File size: 3,240 Bytes
adbccee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_roct_callback10
results: []
---
<!-- 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. -->
# fine_tuned_roct_callback10
This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1842
- Accuracy: 0.9587
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6746 | 0.0309 | 100 | 1.1656 | 0.8788 |
| 0.5117 | 0.0617 | 200 | 0.3858 | 0.8788 |
| 0.3739 | 0.0926 | 300 | 1.0712 | 0.8788 |
| 0.4961 | 0.1235 | 400 | 0.3711 | 0.8274 |
| 0.2688 | 0.1543 | 500 | 0.1956 | 0.8965 |
| 0.2633 | 0.1852 | 600 | 0.2161 | 0.9 |
| 0.3015 | 0.2160 | 700 | 0.2866 | 0.9073 |
| 0.2304 | 0.2469 | 800 | 0.2740 | 0.9017 |
| 0.2114 | 0.2778 | 900 | 0.2462 | 0.9191 |
| 0.2807 | 0.3086 | 1000 | 0.2409 | 0.9125 |
| 0.2323 | 0.3395 | 1100 | 0.3777 | 0.8837 |
| 0.2514 | 0.3704 | 1200 | 0.2062 | 0.9281 |
| 0.2278 | 0.4012 | 1300 | 0.1762 | 0.9351 |
| 0.2099 | 0.4321 | 1400 | 0.1856 | 0.9247 |
| 0.2004 | 0.4630 | 1500 | 0.2237 | 0.9313 |
| 0.2177 | 0.4938 | 1600 | 0.1715 | 0.9313 |
| 0.3046 | 0.5247 | 1700 | 0.1545 | 0.9434 |
| 0.2179 | 0.5556 | 1800 | 0.1713 | 0.9472 |
| 0.1665 | 0.5864 | 1900 | 0.1142 | 0.9549 |
| 0.2066 | 0.6173 | 2000 | 0.1424 | 0.9563 |
| 0.1908 | 0.6481 | 2100 | 0.1284 | 0.9635 |
| 0.145 | 0.6790 | 2200 | 0.1550 | 0.9618 |
| 0.147 | 0.7099 | 2300 | 0.7114 | 0.8826 |
| 0.1634 | 0.7407 | 2400 | 0.1536 | 0.9625 |
| 0.1184 | 0.7716 | 2500 | 0.2507 | 0.9458 |
| 0.1771 | 0.8025 | 2600 | 0.1449 | 0.9583 |
| 0.1399 | 0.8333 | 2700 | 0.2384 | 0.9347 |
| 0.1709 | 0.8642 | 2800 | 0.1296 | 0.9542 |
| 0.1545 | 0.8951 | 2900 | 0.1842 | 0.9587 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0
|