capybara_finetuned_results3
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.6542
video demo : (its pretty bad)
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Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- training_steps: 800
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 15.5311 | 0.0230 | 50 | 14.5422 |
| 8.7477 | 0.0460 | 100 | 9.2952 |
| 7.3554 | 0.0690 | 150 | 7.1992 |
| 6.828 | 0.0920 | 200 | 6.7258 |
| 6.4694 | 0.1150 | 250 | 6.3597 |
| 6.3401 | 0.1381 | 300 | 6.1703 |
| 6.1256 | 0.1611 | 350 | 6.0395 |
| 6.0372 | 0.1841 | 400 | 5.9271 |
| 6.0221 | 0.2071 | 450 | 5.8464 |
| 5.8783 | 0.2301 | 500 | 5.7810 |
| 5.8339 | 0.2531 | 550 | 5.7335 |
| 5.8546 | 0.2761 | 600 | 5.6904 |
| 5.9169 | 0.2991 | 650 | 5.6690 |
| 5.7959 | 0.3221 | 700 | 5.6565 |
| 5.7271 | 0.3451 | 750 | 5.6543 |
| 5.8734 | 0.3682 | 800 | 5.6542 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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Hardware compatibility
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Base model
Qwen/Qwen2.5-0.5B