fineweb-distil-xlstm
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3150
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: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.5458 | 0.08 | 100 | 3.0996 |
2.9415 | 0.16 | 200 | 2.9096 |
2.8028 | 0.24 | 300 | 2.7979 |
2.6877 | 0.32 | 400 | 2.7064 |
2.6105 | 0.4 | 500 | 2.6351 |
2.5406 | 0.48 | 600 | 2.5843 |
2.4982 | 0.56 | 700 | 2.5451 |
2.4888 | 0.64 | 800 | 2.5058 |
2.4339 | 0.72 | 900 | 2.4766 |
2.3962 | 0.8 | 1000 | 2.4500 |
2.3711 | 0.88 | 1100 | 2.4281 |
2.3509 | 0.96 | 1200 | 2.4046 |
2.2915 | 1.04 | 1300 | 2.3911 |
2.2122 | 1.12 | 1400 | 2.3764 |
2.1985 | 1.2 | 1500 | 2.3662 |
2.1937 | 1.28 | 1600 | 2.3508 |
2.191 | 1.3600 | 1700 | 2.3432 |
2.1877 | 1.44 | 1800 | 2.3351 |
2.1629 | 1.52 | 1900 | 2.3276 |
2.1565 | 1.6 | 2000 | 2.3243 |
2.1597 | 1.6800 | 2100 | 2.3203 |
2.1529 | 1.76 | 2200 | 2.3170 |
2.1666 | 1.8400 | 2300 | 2.3157 |
2.1557 | 1.92 | 2400 | 2.3151 |
2.1579 | 2.0 | 2500 | 2.3150 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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