---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- new_dataset
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-manthan_base
  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-manthan_base

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the new_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2246
- Accuracy: 0.9691

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4725        | 0.98  | 12   | 2.4222          | 0.1057   |
| 2.4501        | 1.98  | 24   | 2.2420          | 0.2784   |
| 2.2977        | 2.98  | 36   | 2.0155          | 0.7603   |
| 2.1331        | 3.98  | 48   | 1.8193          | 0.8582   |
| 1.7927        | 4.98  | 60   | 1.6376          | 0.9459   |
| 1.7226        | 5.98  | 72   | 1.4940          | 0.9613   |
| 1.6036        | 6.98  | 84   | 1.3632          | 0.9665   |
| 1.5181        | 7.98  | 96   | 1.2963          | 0.9562   |
| 1.4384        | 8.98  | 108  | 1.2406          | 0.9742   |
| 1.3339        | 9.98  | 120  | 1.2246          | 0.9691   |


### Framework versions

- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 1.14.0
- Tokenizers 0.12.1