Training in progress, step 2500

.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer_config.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,80 +1,57 @@
 ---
 library_name: transformers
+model_name: tiny-audio
 tags:
 - generated_from_trainer
-datasets:
-- generator
-model-index:
-- name: tiny-audio
-  results: []
+- trl
+- sft
+licence: license
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Model Card for tiny-audio
 
-# tiny-audio
+This model is a fine-tuned version of [None](https://huggingface.co/None).
+It has been trained using [TRL](https://github.com/huggingface/trl).
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the generator dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4543
+## Quick start
 
-## Model description
+```python
+from transformers import pipeline
 
-More information needed
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="mazesmazes/tiny-audio", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
+## Training procedure
 
-More information needed
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/alexkroman-alex-kroman/tiny-audio-tts/runs/icuo0fvj) 
 
-## Training procedure
 
-### Training hyperparameters
+This model was trained with SFT.
 
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 8
-- eval_batch_size: 32
-- seed: 123
-- gradient_accumulation_steps: 3
-- total_train_batch_size: 24
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 1000
-- training_steps: 20000
+### Framework versions
 
-### Training results
+- TRL: 0.26.1
+- Transformers: 4.57.3
+- Pytorch: 2.8.0+cu128
+- Datasets: 3.6.0
+- Tokenizers: 0.22.1
 
-| Training Loss | Epoch | Step  | Validation Loss |
-|:-------------:|:-----:|:-----:|:---------------:|
-| 8.8546        | 0.05  | 1000  | 3.8075          |
-| 0.8286        | 0.1   | 2000  | 0.5193          |
-| 0.7909        | 0.15  | 3000  | 0.4701          |
-| 0.6955        | 0.2   | 4000  | 0.4581          |
-| 0.599         | 0.25  | 5000  | 0.4434          |
-| 0.6159        | 0.3   | 6000  | 0.4353          |
-| 0.5764        | 0.35  | 7000  | 0.4260          |
-| 0.602         | 0.05  | 8000  | 0.4298          |
-| 0.5363        | 0.1   | 9000  | 0.4430          |
-| 0.5643        | 0.15  | 10000 | 0.4636          |
-| 0.5135        | 0.2   | 11000 | 0.4423          |
-| 0.4419        | 0.25  | 12000 | 0.4473          |
-| 0.4848        | 0.3   | 13000 | 0.4539          |
-| 0.4692        | 0.35  | 14000 | 0.4481          |
-| 0.5154        | 0.05  | 15000 | 0.4482          |
-| 0.4736        | 0.1   | 16000 | 0.4522          |
-| 0.5097        | 0.15  | 17000 | 0.4537          |
-| 0.4729        | 0.2   | 18000 | 0.4542          |
-| 0.4142        | 0.25  | 19000 | 0.4543          |
-| 0.4718        | 0.3   | 20000 | 0.4543          |
+## Citations
 
 
-### Framework versions
 
-- Transformers 4.57.1
-- Pytorch 2.8.0+cu128
-- Datasets 4.4.1
-- Tokenizers 0.22.1
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

chat_template.jinja

@@ -1,94 +1,6 @@
-{# ───── defaults ───── #}
-{%- if enable_thinking is not defined -%}
-{%- set enable_thinking = true -%}
-{%- endif -%}
-
-{# ───── reasoning mode ───── #}
-{%- if enable_thinking -%}
-  {%- set reasoning_mode = "/think" -%}
-{%- else -%}
-  {%- set reasoning_mode = "/no_think" -%}
-{%- endif -%}
-
-{# ───── header (system message) ───── #}
-{{- "<|im_start|>system\n" -}}
-
-{%- if messages[0].role == "system" -%}
-  {%- set system_message = messages[0].content -%}
-  {%- if "/no_think" in system_message -%}
-    {%- set reasoning_mode = "/no_think" -%}
-  {%- elif "/think" in system_message -%}
-    {%- set reasoning_mode = "/think" -%}
-  {%- endif -%}
-  {%- set custom_instructions = system_message.replace("/no_think", "").replace("/think", "").rstrip() -%}
-{%- endif -%}
-
-{%- if "/system_override" in system_message -%}
-  {{- custom_instructions.replace("/system_override", "").rstrip() -}}
-  {{- "<|im_end|>\n" -}}
-{%- else -%}
-  {{- "## Metadata\n\n" -}}
-  {{- "Knowledge Cutoff Date: June 2025\n" -}}
-  {%- set today = strftime_now("%d %B %Y") -%}
-  {{- "Today Date: " ~ today ~ "\n" -}}
-  {{- "Reasoning Mode: " + reasoning_mode + "\n\n" -}}
-  
-  {{- "## Custom Instructions\n\n" -}}
-  {%- if custom_instructions -%}
-    {{- custom_instructions + "\n\n" -}}
-  {%- elif reasoning_mode == "/think" -%}
-    {{- "You are a helpful AI assistant named SmolLM, trained by Hugging Face. Your role as an assistant involves thoroughly exploring questions through a systematic thinking process before providing the final precise and accurate solutions. This requires engaging in a comprehensive cycle of analysis, summarizing, exploration, reassessment, reflection, backtracking, and iteration to develop well-considered thinking process. Please structure your response into two main sections: Thought and Solution using the specified format: <think> Thought section </think> Solution section. In the Thought section, detail your reasoning process in steps. Each step should include detailed considerations such as analysing questions, summarizing relevant findings, brainstorming new ideas, verifying the accuracy of the current steps, refining any errors, and revisiting previous steps. In the Solution section, based on various attempts, explorations, and reflections from the Thought section, systematically present the final solution that you deem correct. The Solution section should be logical, accurate, and concise and detail necessary steps needed to reach the conclusion.\n\n" -}}
-  {%- else -%}
-    {{- "You are a helpful AI assistant named SmolLM, trained by Hugging Face.\n\n" -}}
-  {%- endif -%}
-
-  {%- if xml_tools or python_tools or tools -%}
-    {{- "### Tools\n\n" -}}
-    {%- if xml_tools or tools -%}
-      {%- if tools -%}
-        {%- set xml_tools = tools -%}
-      {%- endif -%}
-      {%- set ns = namespace(xml_tool_string="You may call one or more functions to assist with the user query.\nYou are provided with function signatures within <tools></tools> XML tags:\n\n<tools>\n") -%}
-      {%- for tool in xml_tools[:] -%} {# The slicing makes sure that xml_tools is a list #}
-        {%- set ns.xml_tool_string = ns.xml_tool_string ~ (tool | string) ~ "\n" -%}
-      {%- endfor -%}
-      {%- set xml_tool_string = ns.xml_tool_string + "</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call>" -%}
-      {{- xml_tool_string -}}
-    {%- endif -%}
-    {%- if python_tools -%}
-      {%- set ns = namespace(python_tool_string="When you send a message containing Python code between '<code>' and '</code>' tags, it will be executed in a stateful Jupyter notebook environment, and you will then be given the output to continued reasoning in an agentic loop.\n\nYou can use the following tools in your python code like regular functions:\n<tools>\n") -%}
-      {%- for tool in python_tools[:] -%} {# The slicing makes sure that python_tools is a list #}
-        {%- set ns.python_tool_string = ns.python_tool_string ~ (tool | string) ~ "\n" -%}
-      {%- endfor -%}
-      {%- set python_tool_string = ns.python_tool_string + "</tools>\n\nThe state persists between code executions: so variables that you define in one step are still available thereafter." -%}
-      {{- python_tool_string -}}
-    {%- endif -%}
-    {{- "\n\n" -}}
-    {{- "<|im_end|>\n" -}}
-  {%- endif -%}
-{%- endif -%}
-{# ───── main loop ───── #}
-{%- for message in messages -%}
-    {%- set content = message.content if message.content is string else "" -%}
-    {%- if message.role == "user" -%}
-        {{ "<|im_start|>" + message.role + "\n"  + content + "<|im_end|>\n" }}
-    {%- elif message.role == "assistant" -%}
-        {% generation %}
-        {%- if reasoning_mode == "/think" -%}
-            {{ "<|im_start|>assistant\n" + content.lstrip("\n") + "<|im_end|>\n" }}
-        {%- else -%}
-            {{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n" + content.lstrip("\n") + "<|im_end|>\n" }}
-        {%- endif -%}
-        {% endgeneration %}
-    {%- elif message.role == "tool" -%}
-    {{ "<|im_start|>" + "user\n"  + content + "<|im_end|>\n" }}
-    {%- endif -%}
-{%- endfor -%}
-{# ───── generation prompt ───── #}
-{%- if add_generation_prompt -%}
-    {%- if reasoning_mode == "/think" -%}
-        {{ "<|im_start|>assistant\n" }}
-    {%- else -%}
-        {{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n"  }}
-    {%- endif -%}
-{%- endif -%}
+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json

@@ -1,195 +1,38 @@
 {
   "architectures": [
-    "ASRModel"
+    "LlamaForCausalLM"
   ],
-  "attn_implementation": "flash_attention_2",
-  "audio_config": {
-    "_name_or_path": "openai/whisper-large-v3-turbo",
-    "activation_dropout": 0.0,
-    "activation_function": "gelu",
-    "apply_spec_augment": false,
-    "architectures": [
-      "WhisperForConditionalGeneration"
-    ],
-    "attention_dropout": 0.0,
-    "bos_token_id": 50257,
-    "classifier_proj_size": 256,
-    "d_model": 1280,
-    "decoder_attention_heads": 20,
-    "decoder_ffn_dim": 5120,
-    "decoder_layerdrop": 0.0,
-    "decoder_layers": 4,
-    "decoder_start_token_id": 50258,
-    "dropout": 0.0,
-    "dtype": "float16",
-    "encoder_attention_heads": 20,
-    "encoder_ffn_dim": 5120,
-    "encoder_layerdrop": 0.0,
-    "encoder_layers": 32,
-    "eos_token_id": 50257,
-    "init_std": 0.02,
-    "mask_feature_length": 10,
-    "mask_feature_min_masks": 0,
-    "mask_feature_prob": 0.0,
-    "mask_time_length": 10,
-    "mask_time_min_masks": 2,
-    "mask_time_prob": 0.05,
-    "max_source_positions": 1500,
-    "max_target_positions": 448,
-    "median_filter_width": 7,
-    "model_type": "whisper",
-    "num_hidden_layers": 32,
-    "num_mel_bins": 128,
-    "pad_token_id": 50257,
-    "scale_embedding": false,
-    "use_cache": true,
-    "use_weighted_layer_sum": false,
-    "vocab_size": 51866
-  },
-  "audio_downsample_rate": 5,
-  "audio_model_id": "openai/whisper-large-v3-turbo",
-  "audio_sample_rate": 16000,
-    "auto_map": {
-    "AutoConfig": "config.ASRConfig",
-    "AutoModel": "voice.model.ASRModelWithVoice",
-    "AutoModelForCausalLM": "voice.model.ASRModelWithVoice"
-  },
-  "custom_pipelines": {
-    "automatic-speech-recognition": {
-      "impl": "asr_pipeline.ASRPipeline",
-      "pt": [
-        "AutoModelForSpeechSeq2Seq"
-      ],
-      "tf": [],
-      "type": "audio"
-    }
-  },
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
   "dtype": "bfloat16",
-  "encoder_dim": 1280,
-  "inference_diversity_penalty": 0.0,
-  "inference_warmup_tokens": 10,
-  "llm_dim": 2048,
-  "max_new_tokens": 128,
-  "min_new_tokens": 1,
-  "model_dtype": "bfloat16",
-  "model_type": "asr_model",
-  "pipeline_tag": "automatic-speech-recognition",
-  "projector_dropout": 0.0,
-  "projector_hidden_dim": 5120,
-  "projector_init_std": 0.02,
-  "projector_pool_stride": 2,
-  "repetition_penalty": 1.05,
-  "system_prompt": "/no_think /system_override",
-  "text_config": {
-    "_name_or_path": "HuggingFaceTB/SmolLM3-3B",
-    "architectures": [
-      "SmolLM3ForCausalLM"
-    ],
-    "attention_bias": false,
-    "attention_dropout": 0.0,
-    "bos_token_id": null,
-    "dtype": "bfloat16",
-    "eos_token_id": 128012,
-    "hidden_act": "silu",
-    "hidden_size": 2048,
-    "initializer_range": 0.02,
-    "intermediate_size": 11008,
-    "layer_types": [
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention",
-      "full_attention"
-    ],
-    "max_position_embeddings": 65536,
-    "max_window_layers": 28,
-    "mlp_bias": false,
-    "model_type": "smollm3",
-    "no_rope_layer_interval": 4,
-    "no_rope_layers": [
-      1,
-      1,
-      1,
-      0,
-      1,
-      1,
-      1,
-      0,
-      1,
-      1,
-      1,
-      0,
-      1,
-      1,
-      1,
-      0,
-      1,
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-      0,
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-      1,
-      0,
-      1,
-      1,
-      1,
-      0,
-      1,
-      1,
-      1,
-      0,
-      1,
-      1,
-      1,
-      0
-    ],
-    "num_attention_heads": 16,
-    "num_hidden_layers": 36,
-    "num_key_value_heads": 4,
-    "pretraining_tp": 2,
-    "rms_norm_eps": 1e-06,
-    "rope_scaling": null,
-    "rope_theta": 5000000.0,
-    "sliding_window": null,
-    "use_cache": false,
-    "use_sliding_window": false,
-    "vocab_size": 128257
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 576,
+  "initializer_range": 0.041666666666666664,
+  "intermediate_size": 1536,
+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 9,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 3,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_interleaved": false,
+  "rope_scaling": null,
+  "rope_theta": 100000,
+  "tie_word_embeddings": true,
+  "transformers.js_config": {
+    "kv_cache_dtype": {
+      "fp16": "float16",
+      "q4f16": "float16"
+    }
   },
-  "text_model_id": "HuggingFaceTB/SmolLM3-3B",
-  "transformers_version": "4.57.1",
-  "use_cache": false,
-  "user_prompt": "Transcribe: <audio>",
-  "vocab_size": 128257
+  "transformers_version": "4.57.3",
+  "use_cache": true,
+  "vocab_size": 114690
 }

generation_config.json

@@ -1,8 +1,10 @@
 {
-  "do_sample": true,
-  "eos_token_id": 128012,
-  "pad_token_id": 128004,
-  "temperature": 0.6,
-  "top_p": 0.95,
-  "transformers_version": "4.57.1"
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": [
+    2,
+    2
+  ],
+  "pad_token_id": 2,
+  "transformers_version": "4.57.3"
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:55f01490cfd7f4ee39d5ccac2e5bace6bf75fd95e68f431604cee1dbcacf1c76
-size 73410040
+oid sha256:2b0574f04cc797cea4c86ca207e912a87e32ab8313566403e027ea760aef5009
+size 344560440

special_tokens_map.json

@@ -1,13 +1,15 @@
 {
   "additional_special_tokens": [
-    {
-      "content": "<audio>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false
-    }
+    "<|im_start|>",
+    "<|im_end|>"
   ],
+  "bos_token": {
+    "content": "<|im_start|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
   "eos_token": {
     "content": "<|im_end|>",
     "lstrip": false,
@@ -15,5 +17,18 @@
     "rstrip": false,
     "single_word": false
   },
-  "pad_token": "<|finetune_right_pad_id|>"
+  "pad_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
 }

tokenizer.json

@@ -1,3 +1,3 @@
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-size 17209003
+oid sha256:d9a0a439f19c272474f9c9213ea2665d1f1cf90eb7f2f6a71b40a919554f078c
+size 15781850

training_args.bin

@@ -1,3 +1,3 @@
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-size 5969
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+size 6289