library_name, tags, model-index
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Aris-293M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2572
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 200
- training_steps: 7630
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.8587 | 0.0655 | 500 | 4.8854 |
| 4.1492 | 0.1311 | 1000 | 4.1392 |
| 3.8591 | 0.1966 | 1500 | 3.8450 |
| 3.7696 | 0.2621 | 2000 | 3.6781 |
| 3.5556 | 0.3277 | 2500 | 3.5741 |
| 3.5234 | 0.3932 | 3000 | 3.4973 |
| 3.4189 | 0.4587 | 3500 | 3.4381 |
| 3.4178 | 0.5242 | 4000 | 3.3871 |
| 3.3873 | 0.5898 | 4500 | 3.3499 |
| 3.3054 | 0.6553 | 5000 | 3.3194 |
| 3.3168 | 0.7208 | 5500 | 3.2948 |
| 3.2871 | 0.7864 | 6000 | 3.2781 |
| 3.2399 | 0.8519 | 6500 | 3.2660 |
| 3.2484 | 0.9174 | 7000 | 3.2593 |
| 3.2665 | 0.9830 | 7500 | 3.2572 |
| 3.2976 | 1.0 | 7630 | 3.2572 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.4.1+cu124
- Datasets 5.0.0
- Tokenizers 0.22.2