excalibur12
/

pic-20s_asr-scr_w2v2-base_002

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 ---
-library_name: transformers
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 ---
-# Model Card for Model ID
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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+model-index:
+- name: pic-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. -->
+# pic-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: 1.4215
+- Per: 0.1497
+- Pcc: 0.6339
+- Ctc Loss: 0.5259
+- Mse Loss: 0.8821
+## 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: 2247
+- training_steps: 22470
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
+| 17.0464       | 3.0   | 2247  | 5.0097          | 0.9979 | 0.6184 | 3.7876   | 1.2860   |
+| 4.3019        | 6.0   | 4494  | 4.2229          | 0.9979 | 0.7055 | 3.7328   | 0.6675   |
+| 3.9383        | 9.0   | 6741  | 4.1717          | 0.9979 | 0.7012 | 3.7059   | 0.7331   |
+| 3.3316        | 12.0  | 8988  | 2.9515          | 0.6216 | 0.6761 | 2.3269   | 0.7956   |
+| 1.5694        | 15.0  | 11235 | 1.8634          | 0.2235 | 0.6674 | 0.8822   | 0.9706   |
+| 0.8929        | 18.0  | 13482 | 1.5733          | 0.1742 | 0.6392 | 0.6657   | 0.8867   |
+| 0.6847        | 21.0  | 15729 | 1.6522          | 0.1613 | 0.6497 | 0.5817   | 1.0250   |
+| 0.5739        | 24.0  | 17976 | 1.4394          | 0.1534 | 0.6165 | 0.5482   | 0.8750   |
+| 0.5063        | 27.0  | 20223 | 1.4105          | 0.1510 | 0.6296 | 0.5322   | 0.8668   |
+| 0.4701        | 30.0  | 22470 | 1.4215          | 0.1497 | 0.6339 | 0.5259   | 0.8821   |
+### Framework versions
+- Transformers 4.38.1
+- Pytorch 2.0.1
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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