End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base-960h
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: sh_sr_model
+  results: []
+---
+
+<!-- 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. -->
+
+# sh_sr_model
+
+This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.0234
+- Wer: 0.4765
+- Cer: 0.8746
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- training_steps: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 0.9917        | 20.0  | 100  | 1.3445          | 0.5882 | 0.8796 |
+| 0.5644        | 40.0  | 200  | 1.3491          | 0.4941 | 0.875  |
+| 0.3946        | 60.0  | 300  | 1.7289          | 0.5412 | 0.8762 |
+| 0.2667        | 80.0  | 400  | 1.8795          | 0.5235 | 0.8762 |
+| 0.2559        | 100.0 | 500  | 2.0205          | 0.5235 | 0.8772 |
+| 0.2148        | 120.0 | 600  | 1.8615          | 0.4941 | 0.875  |
+| 0.1694        | 140.0 | 700  | 1.9697          | 0.4765 | 0.8746 |
+| 0.1793        | 160.0 | 800  | 1.9240          | 0.4706 | 0.8732 |
+| 0.1598        | 180.0 | 900  | 2.0063          | 0.4765 | 0.8742 |
+| 0.1569        | 200.0 | 1000 | 2.0234          | 0.4765 | 0.8746 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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