---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ie
  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. -->

# wav2vec2-base-finetuned-ie

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: 0.9461
- Accuracy: 0.6857

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1913        | 1.0   | 102  | 1.1911          | 0.4374   |
| 1.0238        | 2.0   | 204  | 1.0045          | 0.5529   |
| 0.809         | 3.0   | 306  | 0.9396          | 0.6188   |
| 0.7097        | 4.0   | 408  | 1.2146          | 0.5558   |
| 0.6082        | 5.0   | 510  | 1.2860          | 0.5752   |
| 0.4099        | 6.0   | 612  | 1.3618          | 0.5771   |
| 0.3927        | 7.0   | 714  | 1.1155          | 0.6508   |
| 0.2013        | 8.0   | 816  | 1.3554          | 0.6266   |
| 0.2208        | 9.0   | 918  | 1.7306          | 0.5674   |
| 0.1967        | 10.0  | 1020 | 1.6680          | 0.6004   |
| 0.1563        | 11.0  | 1122 | 1.6125          | 0.6402   |
| 0.0777        | 12.0  | 1224 | 1.7766          | 0.6305   |
| 0.0486        | 13.0  | 1326 | 1.8744          | 0.6324   |
| 0.0594        | 14.0  | 1428 | 1.9529          | 0.6246   |
| 0.0363        | 15.0  | 1530 | 1.8843          | 0.6334   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3