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---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: raw-xlstm
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# raw-xlstm
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.0517
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 40.8489 | 0.32 | 100 | 7.6418 |
| 28.299 | 0.64 | 200 | 6.9708 |
| 26.2015 | 0.96 | 300 | 6.6436 |
| 24.2679 | 1.2784 | 400 | 6.4288 |
| 23.5321 | 1.5984 | 500 | 6.2644 |
| 22.9093 | 1.9184 | 600 | 6.1378 |
| 20.9784 | 2.2368 | 700 | 6.0831 |
| 20.5525 | 2.5568 | 800 | 6.0163 |
| 20.3495 | 2.8768 | 900 | 5.9544 |
| 18.685 | 3.1952 | 1000 | 5.9836 |
| 17.8091 | 3.5152 | 1100 | 5.9750 |
| 17.8559 | 3.8352 | 1200 | 5.9472 |
| 16.4337 | 4.1536 | 1300 | 6.0460 |
| 15.1001 | 4.4736 | 1400 | 6.0802 |
| 15.291 | 4.7936 | 1500 | 6.0832 |
| 14.2383 | 5.112 | 1600 | 6.2050 |
| 12.4653 | 5.432 | 1700 | 6.3012 |
| 12.6628 | 5.752 | 1800 | 6.3316 |
| 12.1045 | 6.0704 | 1900 | 6.4283 |
| 10.2247 | 6.3904 | 2000 | 6.5635 |
| 10.395 | 6.7104 | 2100 | 6.6127 |
| 10.1929 | 7.0288 | 2200 | 6.6716 |
| 8.5996 | 7.3488 | 2300 | 6.8063 |
| 8.6853 | 7.6688 | 2400 | 6.8550 |
| 8.7377 | 7.9888 | 2500 | 6.8878 |
| 7.5955 | 8.3072 | 2600 | 6.9726 |
| 7.6375 | 8.6272 | 2700 | 7.0046 |
| 7.6833 | 8.9472 | 2800 | 7.0211 |
| 7.2457 | 9.2656 | 2900 | 7.0432 |
| 7.2003 | 9.5856 | 3000 | 7.0503 |
| 7.2109 | 9.9056 | 3100 | 7.0517 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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