End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53-spanish
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: wav2vec2-large-xls-r-300m-gn
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_13_0
+      type: common_voice_13_0
+      config: gn
+      split: test
+      args: gn
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.3430613460393091
+---
+
+<!-- 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-large-xls-r-300m-gn
+
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53-spanish](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-spanish) on the common_voice_13_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3713
+- Wer: 0.3431
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.7177        | 3.62  | 400  | 0.3649          | 0.5816 |
+| 0.2738        | 7.24  | 800  | 0.4029          | 0.5024 |
+| 0.1768        | 10.86 | 1200 | 0.3779          | 0.4285 |
+| 0.1128        | 14.48 | 1600 | 0.3929          | 0.4205 |
+| 0.0842        | 18.1  | 2000 | 0.3683          | 0.3916 |
+| 0.0616        | 21.72 | 2400 | 0.3943          | 0.3675 |
+| 0.0461        | 25.34 | 2800 | 0.4127          | 0.3571 |
+| 0.0368        | 28.96 | 3200 | 0.3713          | 0.3431 |
+
+
+### Framework versions
+
+- Transformers 4.35.0.dev0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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