End of training

README.md

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 ---
 library_name: transformers
-tags: []
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+model-index:
+- name: wav2vec2-E30_freq_pause
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
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-## Model Details
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-### Model Description
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+<!-- 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-E30_freq_pause
+
+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: 1.0467
+- Cer: 28.3130
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Cer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 28.57         | 0.1289 | 200  | 4.9399          | 100.0   |
+| 4.9152        | 0.2579 | 400  | 4.7298          | 100.0   |
+| 4.7776        | 0.3868 | 600  | 4.6311          | 98.1732 |
+| 4.7311        | 0.5158 | 800  | 4.5605          | 97.6739 |
+| 4.6426        | 0.6447 | 1000 | 4.5556          | 97.7032 |
+| 4.5691        | 0.7737 | 1200 | 4.5028          | 97.4330 |
+| 4.1847        | 0.9026 | 1400 | 3.9048          | 81.7375 |
+| 3.1837        | 1.0316 | 1600 | 2.8792          | 57.0724 |
+| 2.6116        | 1.1605 | 1800 | 2.4695          | 49.7827 |
+| 2.2803        | 1.2895 | 2000 | 2.2168          | 43.7559 |
+| 2.0438        | 1.4184 | 2200 | 1.9216          | 40.6074 |
+| 1.8919        | 1.5474 | 2400 | 1.7582          | 39.0273 |
+| 1.7295        | 1.6763 | 2600 | 1.6734          | 38.5103 |
+| 1.5832        | 1.8053 | 2800 | 1.5192          | 34.3221 |
+| 1.4426        | 1.9342 | 3000 | 1.4440          | 33.6642 |
+| 1.3355        | 2.0632 | 3200 | 1.3543          | 33.4821 |
+| 1.2131        | 2.1921 | 3400 | 1.2427          | 31.7669 |
+| 1.1532        | 2.3211 | 3600 | 1.2136          | 31.8785 |
+| 1.0948        | 2.4500 | 3800 | 1.1645          | 30.5804 |
+| 1.0283        | 2.5790 | 4000 | 1.1471          | 29.8931 |
+| 1.0085        | 2.7079 | 4200 | 1.0822          | 28.8181 |
+| 0.9753        | 2.8369 | 4400 | 1.0493          | 28.3306 |
+| 0.976         | 2.9658 | 4600 | 1.0467          | 28.3130 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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