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_speed_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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-## Uses
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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_speed_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: 2.6351
+- Cer: 61.7540
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 32.976        | 0.1289 | 200  | 5.1291          | 100.0   |
+| 4.9784        | 0.2579 | 400  | 4.7411          | 100.0   |
+| 4.8371        | 0.3868 | 600  | 4.7057          | 100.0   |
+| 4.7941        | 0.5158 | 800  | 4.7901          | 100.0   |
+| 4.7063        | 0.6447 | 1000 | 4.7698          | 100.0   |
+| 4.6822        | 0.7737 | 1200 | 4.6661          | 100.0   |
+| 4.654         | 0.9026 | 1400 | 4.5412          | 100.0   |
+| 4.5661        | 1.0316 | 1600 | 4.4702          | 99.9765 |
+| 4.4285        | 1.1605 | 1800 | 4.3777          | 98.7253 |
+| 4.1372        | 1.2895 | 2000 | 4.1695          | 97.1452 |
+| 3.8557        | 1.4184 | 2200 | 3.8556          | 73.7664 |
+| 3.5494        | 1.5474 | 2400 | 3.6468          | 70.5298 |
+| 3.2487        | 1.6763 | 2600 | 3.3393          | 68.9086 |
+| 3.0583        | 1.8053 | 2800 | 3.1815          | 67.4636 |
+| 2.9404        | 1.9342 | 3000 | 3.1664          | 67.4283 |
+| 2.8           | 2.0632 | 3200 | 2.9573          | 64.5266 |
+| 2.6974        | 2.1921 | 3400 | 2.8951          | 63.7747 |
+| 2.6229        | 2.3211 | 3600 | 2.8758          | 64.7909 |
+| 2.5551        | 2.4500 | 3800 | 2.8143          | 63.4633 |
+| 2.4771        | 2.5790 | 4000 | 2.7618          | 63.8628 |
+| 2.4412        | 2.7079 | 4200 | 2.7518          | 64.2094 |
+| 2.375         | 2.8369 | 4400 | 2.6586          | 62.5235 |
+| 2.3835        | 2.9658 | 4600 | 2.6351          | 61.7540 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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