excalibur12
/

cmb-20s_asr-scr_w2v2-base_003

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 ---
-library_name: transformers
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 ---
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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+model-index:
+- name: cmb-20s_asr-scr_w2v2-base_003
+  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. -->
+# cmb-20s_asr-scr_w2v2-base_003
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1978
+- Per: 0.1287
+- Pcc: 0.6493
+- Ctc Loss: 0.4014
+- Mse Loss: 0.9499
+## 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: 16
+- eval_batch_size: 1
+- seed: 3333
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 8928
+- training_steps: 89280
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
+| 11.3245       | 3.0   | 8928  | 4.4416          | 0.9956 | 0.6159 | 3.7640   | 0.8975   |
+| 2.9636        | 6.0   | 17856 | 1.4930          | 0.1745 | 0.6638 | 0.6280   | 0.8352   |
+| 1.0327        | 9.0   | 26784 | 1.3313          | 0.1461 | 0.6666 | 0.4797   | 0.8799   |
+| 0.5448        | 12.0  | 35712 | 1.2880          | 0.1394 | 0.6530 | 0.4501   | 0.9425   |
+| 0.1232        | 15.0  | 44640 | 1.0484          | 0.1354 | 0.6481 | 0.4289   | 0.8871   |
+| -0.3248       | 18.0  | 53568 | 1.3777          | 0.1330 | 0.6373 | 0.4163   | 1.1622   |
+| -0.7634       | 21.0  | 62496 | 1.0371          | 0.1312 | 0.6499 | 0.4094   | 1.0824   |
+| -1.2089       | 24.0  | 71424 | 0.4166          | 0.1298 | 0.6454 | 0.4060   | 0.9053   |
+| -1.613        | 27.0  | 80352 | 0.2751          | 0.1290 | 0.6473 | 0.4021   | 0.9426   |
+| -1.8704       | 30.0  | 89280 | 0.1978          | 0.1287 | 0.6493 | 0.4014   | 0.9499   |
+### Framework versions
+- Transformers 4.38.1
+- Pytorch 2.0.1
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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