8575a771-42c9-443b-b82c-1f9fc0b4a8cb
This model is a fine-tuned version of bigscience/bloomz-560m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6902
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: 0.000207
- train_batch_size: 4
- eval_batch_size: 4
- seed: 70
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0003 | 1 | 2.8342 |
| 4.7487 | 0.0170 | 50 | 2.1261 |
| 4.4075 | 0.0341 | 100 | 2.0419 |
| 4.2752 | 0.0511 | 150 | 1.9480 |
| 4.1804 | 0.0681 | 200 | 1.8374 |
| 3.7893 | 0.0851 | 250 | 1.8413 |
| 3.6907 | 0.1022 | 300 | 1.7785 |
| 3.3353 | 0.1192 | 350 | 1.7088 |
| 3.4149 | 0.1362 | 400 | 1.6863 |
| 3.4337 | 0.1532 | 450 | 1.6790 |
| 3.7898 | 0.1703 | 500 | 1.6902 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
bigscience/bloomz-560m