library_name, tags, model-index
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Aris-140M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3110
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: 0.00025
- 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 |
|---|---|---|---|
| 5.0026 | 0.0655 | 500 | 4.9335 |
| 4.1512 | 0.1311 | 1000 | 4.1450 |
| 3.9029 | 0.1966 | 1500 | 3.8596 |
| 3.7558 | 0.2621 | 2000 | 3.7075 |
| 3.5920 | 0.3277 | 2500 | 3.6100 |
| 3.5657 | 0.3932 | 3000 | 3.5328 |
| 3.4994 | 0.4587 | 3500 | 3.4764 |
| 3.4811 | 0.5242 | 4000 | 3.4332 |
| 3.4043 | 0.5898 | 4500 | 3.3970 |
| 3.3963 | 0.6553 | 5000 | 3.3697 |
| 3.3784 | 0.7208 | 5500 | 3.3471 |
| 3.3817 | 0.7864 | 6000 | 3.3304 |
| 3.3694 | 0.8519 | 6500 | 3.3189 |
| 3.3337 | 0.9174 | 7000 | 3.3129 |
| 3.3679 | 0.9830 | 7500 | 3.3111 |
| 3.3503 | 1.0 | 7630 | 3.3110 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.6.0+cu124
- Datasets 5.0.0
- Tokenizers 0.22.2