---
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: 1.0066
- Accuracy: 0.6487

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1544        | 1.0   | 102  | 1.1369          | 0.5063   |
| 1.0574        | 2.0   | 204  | 1.0677          | 0.5121   |
| 0.8303        | 3.0   | 306  | 0.9213          | 0.6091   |
| 0.7753        | 4.0   | 408  | 1.0430          | 0.5926   |
| 0.6142        | 5.0   | 510  | 1.1218          | 0.6033   |
| 0.5152        | 6.0   | 612  | 1.1629          | 0.6188   |
| 0.51          | 7.0   | 714  | 0.9371          | 0.6838   |
| 0.2368        | 8.0   | 816  | 1.2314          | 0.6343   |
| 0.2315        | 9.0   | 918  | 1.3838          | 0.6285   |
| 0.2324        | 10.0  | 1020 | 1.3675          | 0.6489   |
| 0.1919        | 11.0  | 1122 | 1.5164          | 0.6372   |
| 0.0962        | 12.0  | 1224 | 1.5281          | 0.6440   |
| 0.0851        | 13.0  | 1326 | 1.5718          | 0.6479   |
| 0.0358        | 14.0  | 1428 | 1.6729          | 0.6508   |
| 0.0754        | 15.0  | 1530 | 1.6681          | 0.6528   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2