End of training

README.md

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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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