Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-luo_cv_fleurs_19h
+  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. -->
+
+# w2v-bert-2.0-luo_cv_fleurs_19h
+
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4323
+- Wer: 0.3056
+- Cer: 0.0952
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- 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_ratio: 0.1
+- training_steps: 100000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
+| 0.698         | 6.4935  | 1000 | 0.7171          | 0.5988 | 0.1884 |
+| 0.2666        | 12.9870 | 2000 | 0.3521          | 0.3862 | 0.1107 |
+| 0.1497        | 19.4805 | 3000 | 0.2914          | 0.3351 | 0.0979 |
+| 0.0802        | 25.9740 | 4000 | 0.2682          | 0.2976 | 0.0931 |
+| 0.053         | 32.4675 | 5000 | 0.3036          | 0.3060 | 0.0913 |
+| 0.0309        | 38.9610 | 6000 | 0.3689          | 0.2906 | 0.0939 |
+| 0.0245        | 45.4545 | 7000 | 0.4164          | 0.3792 | 0.1007 |
+| 0.0122        | 51.9481 | 8000 | 0.3996          | 0.3166 | 0.0964 |
+| 0.0088        | 58.4416 | 9000 | 0.4323          | 0.3056 | 0.0952 |
+
+
+### Framework versions
+
+- Transformers 4.48.1
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

model.safetensors

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