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---
base_model: openai/whisper-medium
datasets:
- generator
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: whisper-medium-sb-lug-eng-v2
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-medium-sb-lug-eng-v2
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1255
- Wer Lug: 0.124
- Wer Eng: 0.171
- Wer Mean: 0.147
- Cer Lug: 0.028
- Cer Eng: 0.164
- Cer Mean: 0.096
## 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Lug | Wer Eng | Wer Mean | Cer Lug | Cer Eng | Cer Mean |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------:|:-------:|:-------:|:--------:|
| 0.7222 | 0.1 | 500 | 0.2662 | 0.391 | 0.146 | 0.268 | 0.085 | 0.104 | 0.095 |
| 0.5452 | 0.2 | 1000 | 0.1894 | 0.223 | 0.058 | 0.141 | 0.05 | 0.034 | 0.042 |
| 0.4172 | 0.3 | 1500 | 0.1764 | 0.199 | 0.276 | 0.238 | 0.043 | 0.269 | 0.156 |
| 0.3949 | 0.4 | 2000 | 0.1583 | 0.177 | 0.035 | 0.106 | 0.039 | 0.017 | 0.028 |
| 0.3626 | 0.5 | 2500 | 0.1508 | 0.153 | 0.157 | 0.155 | 0.035 | 0.122 | 0.078 |
| 0.3467 | 0.6 | 3000 | 0.1397 | 0.14 | 0.258 | 0.199 | 0.033 | 0.213 | 0.123 |
| 0.3443 | 0.7 | 3500 | 0.1333 | 0.139 | 0.044 | 0.092 | 0.032 | 0.027 | 0.029 |
| 0.3169 | 0.8 | 4000 | 0.1297 | 0.129 | 0.027 | 0.078 | 0.029 | 0.011 | 0.02 |
| 0.3276 | 0.9 | 4500 | 0.1264 | 0.124 | 0.086 | 0.105 | 0.028 | 0.058 | 0.043 |
| 0.317 | 1.0 | 5000 | 0.1255 | 0.124 | 0.171 | 0.147 | 0.028 | 0.164 | 0.096 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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