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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: raw-xlstm |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# raw-xlstm |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 7.0517 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 40.8489 | 0.32 | 100 | 7.6418 | |
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| 28.299 | 0.64 | 200 | 6.9708 | |
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| 26.2015 | 0.96 | 300 | 6.6436 | |
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| 24.2679 | 1.2784 | 400 | 6.4288 | |
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| 23.5321 | 1.5984 | 500 | 6.2644 | |
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| 22.9093 | 1.9184 | 600 | 6.1378 | |
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| 20.9784 | 2.2368 | 700 | 6.0831 | |
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| 20.5525 | 2.5568 | 800 | 6.0163 | |
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| 20.3495 | 2.8768 | 900 | 5.9544 | |
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| 18.685 | 3.1952 | 1000 | 5.9836 | |
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| 17.8091 | 3.5152 | 1100 | 5.9750 | |
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| 17.8559 | 3.8352 | 1200 | 5.9472 | |
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| 16.4337 | 4.1536 | 1300 | 6.0460 | |
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| 15.1001 | 4.4736 | 1400 | 6.0802 | |
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| 15.291 | 4.7936 | 1500 | 6.0832 | |
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| 14.2383 | 5.112 | 1600 | 6.2050 | |
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| 12.4653 | 5.432 | 1700 | 6.3012 | |
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| 12.6628 | 5.752 | 1800 | 6.3316 | |
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| 12.1045 | 6.0704 | 1900 | 6.4283 | |
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| 10.2247 | 6.3904 | 2000 | 6.5635 | |
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| 10.395 | 6.7104 | 2100 | 6.6127 | |
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| 10.1929 | 7.0288 | 2200 | 6.6716 | |
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| 8.5996 | 7.3488 | 2300 | 6.8063 | |
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| 8.6853 | 7.6688 | 2400 | 6.8550 | |
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| 8.7377 | 7.9888 | 2500 | 6.8878 | |
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| 7.5955 | 8.3072 | 2600 | 6.9726 | |
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| 7.6375 | 8.6272 | 2700 | 7.0046 | |
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| 7.6833 | 8.9472 | 2800 | 7.0211 | |
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| 7.2457 | 9.2656 | 2900 | 7.0432 | |
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| 7.2003 | 9.5856 | 3000 | 7.0503 | |
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| 7.2109 | 9.9056 | 3100 | 7.0517 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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