distil-xlstm
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2544
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.6092 | 0.08 | 100 | 1.9068 |
1.8079 | 0.16 | 200 | 1.6734 |
1.6488 | 0.24 | 300 | 1.5536 |
1.5613 | 0.32 | 400 | 1.4719 |
1.4719 | 0.4 | 500 | 1.4070 |
1.4242 | 0.48 | 600 | 1.3625 |
1.3846 | 0.56 | 700 | 1.3247 |
1.3479 | 0.64 | 800 | 1.2999 |
1.3265 | 0.72 | 900 | 1.2787 |
1.3035 | 0.8 | 1000 | 1.2644 |
1.278 | 0.88 | 1100 | 1.2571 |
1.2956 | 0.96 | 1200 | 1.2544 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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