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---
license: apache-2.0
base_model: OthmaneJ/distil-wav2vec2
tags:
- generated_from_trainer
datasets:
- OthmaneJ/distil-wav2vec2
metrics:
- accuracy
model-index:
- name: distil-wav2vec2-finetuned-giga-speech
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: Giga Speech
type: OthmaneJ/distil-wav2vec2
config: xs
split: train
args: xs
metrics:
- name: Accuracy
type: accuracy
value: 0.8881789137380192
---
<!-- 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. -->
# distil-wav2vec2-finetuned-giga-speech
This model is a fine-tuned version of [OthmaneJ/distil-wav2vec2](https://huggingface.co/OthmaneJ/distil-wav2vec2) on the Giga Speech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4271
- Accuracy: 0.8882
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4425 | 1.0 | 1057 | 1.3045 | 0.5399 |
| 0.796 | 2.0 | 2114 | 0.8516 | 0.7284 |
| 0.9685 | 3.0 | 3171 | 0.5054 | 0.8626 |
| 0.5623 | 4.0 | 4228 | 0.4271 | 0.8882 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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