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-E10_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-E10_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: 1.2932
+- Cer: 28.7124
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 27.1594       | 0.1289 | 200  | 4.8622          | 100.0   |
+| 4.9998        | 0.2579 | 400  | 4.7518          | 100.0   |
+| 4.8719        | 0.3868 | 600  | 4.7669          | 100.0   |
+| 4.809         | 0.5158 | 800  | 4.6593          | 100.0   |
+| 4.7354        | 0.6447 | 1000 | 4.5911          | 100.0   |
+| 4.6679        | 0.7737 | 1200 | 4.6423          | 99.3773 |
+| 4.136         | 0.9026 | 1400 | 3.9276          | 77.9077 |
+| 3.1108        | 1.0316 | 1600 | 2.9616          | 56.7845 |
+| 2.6314        | 1.1605 | 1800 | 2.7039          | 51.9619 |
+| 2.2786        | 1.2895 | 2000 | 2.3306          | 45.8823 |
+| 2.0348        | 1.4184 | 2200 | 2.1354          | 40.5721 |
+| 1.8952        | 1.5474 | 2400 | 1.9727          | 39.7086 |
+| 1.7053        | 1.6763 | 2600 | 1.8535          | 37.7996 |
+| 1.5809        | 1.8053 | 2800 | 1.7608          | 36.7246 |
+| 1.4968        | 1.9342 | 3000 | 1.6229          | 33.2531 |
+| 1.349         | 2.0632 | 3200 | 1.6171          | 33.6290 |
+| 1.2592        | 2.1921 | 3400 | 1.5156          | 32.9300 |
+| 1.2043        | 2.3211 | 3600 | 1.4406          | 30.7977 |
+| 1.1418        | 2.4500 | 3800 | 1.3878          | 29.5172 |
+| 1.1157        | 2.5790 | 4000 | 1.3441          | 29.1060 |
+| 1.0653        | 2.7079 | 4200 | 1.3052          | 27.9605 |
+| 1.0451        | 2.8369 | 4400 | 1.2943          | 28.5656 |
+| 1.0225        | 2.9658 | 4600 | 1.2932          | 28.7124 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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