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-E50_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-E50_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: 1.0444
+- Cer: 21.8625
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- 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     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 37.5369       | 0.1289 | 200  | 5.2051          | 100.0   |
+| 4.8991        | 0.2579 | 400  | 4.6157          | 100.0   |
+| 4.7556        | 0.3868 | 600  | 4.6579          | 100.0   |
+| 4.7401        | 0.5158 | 800  | 4.7246          | 100.0   |
+| 4.6787        | 0.6447 | 1000 | 4.5941          | 100.0   |
+| 4.6531        | 0.7737 | 1200 | 4.5238          | 100.0   |
+| 4.5631        | 0.9026 | 1400 | 4.3757          | 100.0   |
+| 3.8885        | 1.0316 | 1600 | 3.1641          | 57.0682 |
+| 2.9165        | 1.1605 | 1800 | 2.6892          | 47.8202 |
+| 2.4332        | 1.2895 | 2000 | 2.2163          | 40.8226 |
+| 2.1146        | 1.4184 | 2200 | 1.9082          | 35.0705 |
+| 1.9011        | 1.5474 | 2400 | 1.8199          | 35.3702 |
+| 1.7622        | 1.6763 | 2600 | 1.6833          | 32.0564 |
+| 1.6191        | 1.8053 | 2800 | 1.5709          | 30.7109 |
+| 1.4782        | 1.9342 | 3000 | 1.4401          | 28.7427 |
+| 1.3359        | 2.0632 | 3200 | 1.3604          | 27.1093 |
+| 1.2158        | 2.1921 | 3400 | 1.2156          | 24.7650 |
+| 1.1436        | 2.3211 | 3600 | 1.1927          | 24.3948 |
+| 1.1092        | 2.4500 | 3800 | 1.1650          | 24.4712 |
+| 1.0546        | 2.5790 | 4000 | 1.0929          | 22.8966 |
+| 1.0207        | 2.7079 | 4200 | 1.0990          | 22.8790 |
+| 0.9799        | 2.8369 | 4400 | 1.0580          | 22.2679 |
+| 0.9561        | 2.9658 | 4600 | 1.0444          | 21.8625 |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

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