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---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_eli5_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_eli5_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: 0.1230
- Accuracy: 0.9747
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7967 | 0.0210 | 100 | 0.3296 | 0.8710 |
| 0.5957 | 0.0421 | 200 | 0.5430 | 0.8329 |
| 0.386 | 0.0631 | 300 | 0.6117 | 0.8694 |
| 0.3981 | 0.0841 | 400 | 0.3349 | 0.9129 |
| 0.3357 | 0.1052 | 500 | 0.2388 | 0.9117 |
| 0.2831 | 0.1262 | 600 | 0.4056 | 0.9063 |
| 0.4625 | 0.1472 | 700 | 0.2346 | 0.9058 |
| 0.3478 | 0.1683 | 800 | 0.1944 | 0.9259 |
| 0.2524 | 0.1893 | 900 | 0.3200 | 0.9203 |
| 0.3523 | 0.2103 | 1000 | 0.3342 | 0.9113 |
| 0.2756 | 0.2314 | 1100 | 0.2443 | 0.9423 |
| 0.2814 | 0.2524 | 1200 | 0.2346 | 0.9349 |
| 0.2636 | 0.2735 | 1300 | 0.5285 | 0.9018 |
| 0.2491 | 0.2945 | 1400 | 0.1802 | 0.9472 |
| 0.2328 | 0.3155 | 1500 | 0.2347 | 0.9468 |
| 0.2113 | 0.3366 | 1600 | 0.2146 | 0.9453 |
| 0.2342 | 0.3576 | 1700 | 0.2253 | 0.9406 |
| 0.2102 | 0.3786 | 1800 | 0.1987 | 0.9515 |
| 0.1518 | 0.3997 | 1900 | 0.2878 | 0.9373 |
| 0.2326 | 0.4207 | 2000 | 0.2071 | 0.9489 |
| 0.2018 | 0.4417 | 2100 | 0.1554 | 0.9498 |
| 0.1924 | 0.4628 | 2200 | 0.1812 | 0.9515 |
| 0.2139 | 0.4838 | 2300 | 0.3613 | 0.9302 |
| 0.2801 | 0.5048 | 2400 | 0.1490 | 0.9527 |
| 0.1979 | 0.5259 | 2500 | 0.1786 | 0.9546 |
| 0.1695 | 0.5469 | 2600 | 0.1765 | 0.9536 |
| 0.1541 | 0.5679 | 2700 | 0.1390 | 0.9631 |
| 0.1527 | 0.5890 | 2800 | 0.1198 | 0.9598 |
| 0.1711 | 0.6100 | 2900 | 0.1841 | 0.9593 |
| 0.2014 | 0.6310 | 3000 | 0.1497 | 0.9621 |
| 0.1174 | 0.6521 | 3100 | 0.1464 | 0.9671 |
| 0.1452 | 0.6731 | 3200 | 0.1323 | 0.9652 |
| 0.1367 | 0.6942 | 3300 | 0.1316 | 0.9659 |
| 0.1798 | 0.7152 | 3400 | 0.2200 | 0.9553 |
| 0.1683 | 0.7362 | 3500 | 0.1399 | 0.9655 |
| 0.1426 | 0.7573 | 3600 | 0.1146 | 0.9726 |
| 0.203 | 0.7783 | 3700 | 0.1601 | 0.9666 |
| 0.1452 | 0.7993 | 3800 | 0.1491 | 0.9692 |
| 0.1602 | 0.8204 | 3900 | 0.1251 | 0.9740 |
| 0.1451 | 0.8414 | 4000 | 0.1192 | 0.9747 |
| 0.14 | 0.8624 | 4100 | 0.1441 | 0.9695 |
| 0.158 | 0.8835 | 4200 | 0.1428 | 0.9692 |
| 0.1211 | 0.9045 | 4300 | 0.1841 | 0.9619 |
| 0.1324 | 0.9255 | 4400 | 0.1587 | 0.9657 |
| 0.1153 | 0.9466 | 4500 | 0.1411 | 0.9697 |
| 0.1321 | 0.9676 | 4600 | 0.1230 | 0.9747 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0
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