my_asr_model_2 / README.md
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- wer
model-index:
- name: my_asr_model_2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: minds14
type: minds14
config: en-US
split: train[:100]
args: en-US
metrics:
- name: Wer
type: wer
value: 1.0
---
<!-- 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. -->
# my_asr_model_2
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1785
- Wer: 1.0
## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 3.0949 | 20.0 | 100 | 3.1923 | 1.0 |
| 3.0836 | 40.0 | 200 | 3.1769 | 1.0 |
| 3.0539 | 60.0 | 300 | 3.1766 | 1.0 |
| 3.0687 | 80.0 | 400 | 3.1853 | 1.0 |
| 3.0649 | 100.0 | 500 | 3.1785 | 1.0 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2