---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: model_sh_intit_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. -->

# model_sh_intit_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: 1.4880
- Wer: 0.3617
- Cer: 0.9396

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.9874        | 20.0  | 100  | 1.6657          | 0.5234 | 0.9457 |
| 0.5576        | 40.0  | 200  | 1.0859          | 0.4426 | 0.9422 |
| 0.399         | 60.0  | 300  | 1.2627          | 0.3957 | 0.9406 |
| 0.2509        | 80.0  | 400  | 1.3391          | 0.3830 | 0.9405 |
| 0.2643        | 100.0 | 500  | 1.4182          | 0.3787 | 0.9401 |
| 0.1931        | 120.0 | 600  | 1.3800          | 0.3915 | 0.9403 |
| 0.1553        | 140.0 | 700  | 1.4751          | 0.3957 | 0.9402 |
| 0.1679        | 160.0 | 800  | 1.4633          | 0.3660 | 0.9397 |
| 0.1642        | 180.0 | 900  | 1.5003          | 0.3617 | 0.9397 |
| 0.1286        | 200.0 | 1000 | 1.4880          | 0.3617 | 0.9396 |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1