---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: pic_asr-scr_w2v2-base_002
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pic_asr-scr_w2v2-base_002

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: 0.9265
- Per: 0.1166
- Pcc: 0.6564
- Ctc Loss: 0.4120
- Mse Loss: 0.8926

## 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: 16
- eval_batch_size: 1
- seed: 2222
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 749
- training_steps: 7490

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 11.7735       | 1.0   | 749  | 4.6360          | 0.9994 | 0.5280 | 3.7649   | 1.0658   |
| 3.8371        | 2.0   | 1498 | 2.1765          | 0.4402 | 0.6444 | 1.3986   | 0.8505   |
| 1.5597        | 3.0   | 2247 | 1.4609          | 0.1505 | 0.6303 | 0.5347   | 0.8698   |
| 1.0295        | 4.0   | 2996 | 1.3057          | 0.1356 | 0.6506 | 0.4765   | 0.8171   |
| 0.6253        | 5.0   | 3745 | 1.4002          | 0.1293 | 0.6472 | 0.4443   | 0.9477   |
| 0.2398        | 6.0   | 4494 | 1.0775          | 0.1251 | 0.6506 | 0.4249   | 0.8004   |
| -0.1329       | 7.0   | 5243 | 1.1855          | 0.1213 | 0.6509 | 0.4299   | 0.9175   |
| -0.4801       | 8.0   | 5992 | 1.2405          | 0.1194 | 0.6515 | 0.4101   | 1.0046   |
| -0.7409       | 9.0   | 6741 | 0.9340          | 0.1169 | 0.6554 | 0.4097   | 0.8839   |
| -0.8966       | 10.0  | 7490 | 0.9265          | 0.1166 | 0.6564 | 0.4120   | 0.8926   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2