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-Y_speed2
+  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-Y_speed2
+
+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: 1.9944
+- Cer: 38.7688
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 43.7135       | 0.1289 | 200  | 5.1032          | 100.0   |
+| 5.0439        | 0.2579 | 400  | 4.6765          | 100.0   |
+| 4.8774        | 0.3868 | 600  | 4.6557          | 100.0   |
+| 4.8641        | 0.5158 | 800  | 4.6426          | 100.0   |
+| 4.7995        | 0.6447 | 1000 | 4.6472          | 100.0   |
+| 4.7762        | 0.7737 | 1200 | 4.6153          | 100.0   |
+| 4.7579        | 0.9026 | 1400 | 4.6154          | 100.0   |
+| 4.7082        | 1.0316 | 1600 | 4.6180          | 100.0   |
+| 4.6786        | 1.1605 | 1800 | 4.5371          | 100.0   |
+| 4.6438        | 1.2895 | 2000 | 4.5289          | 100.0   |
+| 4.5663        | 1.4184 | 2200 | 4.4416          | 100.0   |
+| 4.503         | 1.5474 | 2400 | 4.3983          | 99.3421 |
+| 4.2564        | 1.6763 | 2600 | 4.0853          | 82.7714 |
+| 3.7092        | 1.8053 | 2800 | 3.2871          | 61.8656 |
+| 3.071         | 1.9342 | 3000 | 2.9127          | 53.0663 |
+| 2.704         | 2.0632 | 3200 | 2.6764          | 49.4302 |
+| 2.4656        | 2.1921 | 3400 | 2.4448          | 45.2420 |
+| 2.2855        | 2.3211 | 3600 | 2.2835          | 42.6339 |
+| 2.1728        | 2.4500 | 3800 | 2.2042          | 42.0876 |
+| 2.0623        | 2.5790 | 4000 | 2.1021          | 39.8144 |
+| 1.9909        | 2.7079 | 4200 | 2.0544          | 39.5266 |
+| 1.9129        | 2.8369 | 4400 | 2.0083          | 38.7453 |
+| 1.9151        | 2.9658 | 4600 | 1.9944          | 38.7688 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

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