Model save

README.md

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+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: mms-1b-bigcgen-male-5hrs-model
+  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. -->
+
+# mms-1b-bigcgen-male-5hrs-model
+
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4407
+- Wer: 0.4520
+
+## 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: 0.0003
+- 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: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 30.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 12.4451       | 0.3106 | 100  | 1.2035          | 0.8329 |
+| 1.6342        | 0.6211 | 200  | 0.6175          | 0.5759 |
+| 1.5403        | 0.9317 | 300  | 0.5695          | 0.5535 |
+| 1.3778        | 1.2422 | 400  | 0.5524          | 0.5359 |
+| 1.4572        | 1.5528 | 500  | 0.5302          | 0.5172 |
+| 1.4042        | 1.8634 | 600  | 0.5179          | 0.5266 |
+| 1.4053        | 2.1739 | 700  | 0.5029          | 0.5143 |
+| 1.2782        | 2.4845 | 800  | 0.4701          | 0.4864 |
+| 1.2541        | 2.7950 | 900  | 0.4585          | 0.4867 |
+| 1.1672        | 3.1056 | 1000 | 0.4728          | 0.4862 |
+| 1.1205        | 3.4161 | 1100 | 0.4558          | 0.4794 |
+| 1.1699        | 3.7267 | 1200 | 0.4520          | 0.4811 |
+| 1.2418        | 4.0373 | 1300 | 0.4495          | 0.4751 |
+| 1.071         | 4.3478 | 1400 | 0.4487          | 0.4737 |
+| 1.078         | 4.6584 | 1500 | 0.4446          | 0.4761 |
+| 1.2474        | 4.9689 | 1600 | 0.4437          | 0.4626 |
+| 1.1127        | 5.2795 | 1700 | 0.4380          | 0.4657 |
+| 1.1761        | 5.5901 | 1800 | 0.4480          | 0.4674 |
+| 1.0997        | 5.9006 | 1900 | 0.4470          | 0.4653 |
+| 1.1203        | 6.2112 | 2000 | 0.4421          | 0.4614 |
+| 1.0749        | 6.5217 | 2100 | 0.4344          | 0.4506 |
+| 1.1156        | 6.8323 | 2200 | 0.4354          | 0.4511 |
+| 1.0404        | 7.1429 | 2300 | 0.4364          | 0.4535 |
+| 1.1081        | 7.4534 | 2400 | 0.4377          | 0.4516 |
+| 1.0535        | 7.7640 | 2500 | 0.4407          | 0.4520 |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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