README.md

metadata

library_name: transformers
tags:
  - generated_from_trainer
model-index:
  - name: tiny-audio
    results: []

tiny-audio

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2566

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 936
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 500
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.2888	0.0149	1000	0.2819
0.3565	0.0298	2000	0.2919
0.3189	0.0447	3000	0.2879
0.3274	0.0596	4000	0.2929
0.3231	0.0745	5000	0.2870
0.3270	0.0894	6000	0.2853
0.3486	0.1043	7000	0.2860
0.3066	0.1192	8000	0.2865
0.3487	0.1341	9000	0.2866
0.3307	0.1490	10000	0.2871
0.3419	0.1639	11000	0.2852
0.3601	0.1788	12000	0.2848
0.3156	0.1936	13000	0.2860
0.3098	0.2085	14000	0.2830
0.3133	0.2234	15000	0.2851
0.3269	0.2383	16000	0.2826
0.3257	0.2532	17000	0.2822
0.3281	0.2681	18000	0.2822
0.3941	0.2830	19000	0.2813
0.3875	0.2979	20000	0.2854
0.3214	0.3128	21000	0.2795
0.2914	0.3277	22000	0.2792
0.2951	0.3426	23000	0.2805
0.3343	0.3575	24000	0.2779
0.3252	0.3724	25000	0.2771
0.3027	0.3873	26000	0.2768
0.3287	0.4022	27000	0.2759
0.3208	0.4171	28000	0.2749
0.3402	0.4320	29000	0.2730
0.2928	0.4469	30000	0.2726
0.3085	0.4618	31000	0.2737
0.3073	0.4767	32000	0.2705
0.3471	0.4916	33000	0.2708
0.2945	0.5065	34000	0.2690
0.3294	0.5214	35000	0.2696
0.3095	0.5363	36000	0.2679
0.3152	0.5512	37000	0.2659
0.3035	0.5660	38000	0.2674
0.3342	0.5809	39000	0.2656
0.3242	0.5958	40000	0.2653
0.2789	0.6107	41000	0.2643
0.3082	0.6256	42000	0.2643
0.3174	0.6405	43000	0.2633
0.2730	0.6554	44000	0.2628
0.2934	0.6703	45000	0.2609
0.2944	0.6852	46000	0.2606
0.3111	0.7001	47000	0.2614
0.3431	0.7150	48000	0.2605
0.3226	0.7299	49000	0.2601
0.2735	0.7448	50000	0.2591
0.3208	0.7597	51000	0.2590
0.3208	0.7746	52000	0.2584
0.3021	0.7895	53000	0.2578
0.2730	0.8044	54000	0.2583
0.2938	0.8193	55000	0.2581
0.2894	0.8342	56000	0.2574
0.2781	0.8491	57000	0.2572
0.3003	0.8640	58000	0.2568
0.2719	0.8789	59000	0.2568
0.2878	0.8938	60000	0.2567
0.3058	0.9087	61000	0.2568
0.3036	0.9236	62000	0.2568
0.3050	0.9384	63000	0.2568
0.3244	0.9533	64000	0.2567
0.3187	0.9682	65000	0.2566
0.3016	0.9831	66000	0.2566
0.2697	0.9980	67000	0.2566

Framework versions

• Transformers 5.0.0.dev0
• Pytorch 2.8.0+cu128
• Datasets 3.6.0
• Tokenizers 0.22.1