Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Wav2vec2-fula
+  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. -->
+
+# Wav2vec2-fula
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3185
+- Wer: 0.5379
+
+## 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: 5e-05
+- 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: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 60.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
+|:-------------:|:------:|:-----:|:---------------:|:------:|
+| 3.1344        | 0.3437 | 500   | 3.0935          | 1.0    |
+| 0.7323        | 0.6874 | 1000  | 0.6304          | 0.7120 |
+| 0.5416        | 1.0316 | 1500  | 0.4785          | 0.6491 |
+| 0.4479        | 1.3753 | 2000  | 0.4202          | 0.6207 |
+| 0.4541        | 1.7190 | 2500  | 0.3851          | 0.6006 |
+| 0.365         | 2.0632 | 3000  | 0.3701          | 0.5885 |
+| 0.3433        | 2.4069 | 3500  | 0.3648          | 0.5797 |
+| 0.3561        | 2.7506 | 4000  | 0.3438          | 0.5716 |
+| 0.3237        | 3.0949 | 4500  | 0.3647          | 0.5677 |
+| 0.322         | 3.4386 | 5000  | 0.3427          | 0.5638 |
+| 0.2921        | 3.7823 | 5500  | 0.3345          | 0.5604 |
+| 0.3037        | 4.1265 | 6000  | 0.3352          | 0.5541 |
+| 0.2695        | 4.4702 | 6500  | 0.3202          | 0.5515 |
+| 0.2804        | 4.8139 | 7000  | 0.3353          | 0.5525 |
+| 0.2908        | 5.1581 | 7500  | 0.3384          | 0.5485 |
+| 0.2646        | 5.5018 | 8000  | 0.3164          | 0.5462 |
+| 0.2982        | 5.8455 | 8500  | 0.3143          | 0.5455 |
+| 0.2978        | 6.1897 | 9000  | 0.3218          | 0.5424 |
+| 0.288         | 6.5334 | 9500  | 0.3152          | 0.5418 |
+| 0.2706        | 6.8771 | 10000 | 0.3211          | 0.5398 |
+| 0.3008        | 7.2213 | 10500 | 0.3266          | 0.5398 |
+| 0.2674        | 7.5650 | 11000 | 0.3185          | 0.5379 |
+
+
+### Framework versions
+
+- Transformers 4.50.3
+- Pytorch 2.7.0+cu126
+- Datasets 3.5.0
+- Tokenizers 0.21.1

model.safetensors

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