whisper-tiny-metal / README.md
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---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Tiny Metal - Juan Pablo Diaz
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. -->
# Whisper Tiny Metal - Juan Pablo Diaz
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Gutural Scream and Metal Vocals dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6780
- Wer: 79.9061
## 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: 16
- 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_steps: 500
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0844 | 9.62 | 1000 | 1.3967 | 104.6055 |
| 0.0018 | 19.23 | 2000 | 1.5861 | 93.5465 |
| 0.0008 | 28.85 | 3000 | 1.6552 | 78.9381 |
| 0.0006 | 38.46 | 4000 | 1.6780 | 79.9061 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3