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---
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V2 Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 eu
type: mozilla-foundation/common_voice_13_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 11.339057880027543
---
<!-- 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 Large-V2 Basque
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3943
- Wer: 11.3391
## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0355 | 4.01 | 1000 | 0.2616 | 14.8224 |
| 0.0079 | 9.01 | 2000 | 0.2777 | 13.5202 |
| 0.0041 | 14.01 | 3000 | 0.2764 | 12.7364 |
| 0.0047 | 19.0 | 4000 | 0.2932 | 12.6939 |
| 0.004 | 24.0 | 5000 | 0.2969 | 12.7992 |
| 0.0019 | 29.0 | 6000 | 0.3066 | 12.6008 |
| 0.004 | 33.01 | 7000 | 0.2973 | 12.6696 |
| 0.0007 | 38.01 | 8000 | 0.3253 | 12.2686 |
| 0.0006 | 43.01 | 9000 | 0.3391 | 12.5319 |
| 0.0009 | 48.01 | 10000 | 0.3303 | 12.2767 |
| 0.0004 | 53.0 | 11000 | 0.3383 | 12.0195 |
| 0.0003 | 58.0 | 12000 | 0.3398 | 11.7441 |
| 0.0005 | 63.0 | 13000 | 0.3396 | 11.8778 |
| 0.0001 | 67.01 | 14000 | 0.3544 | 11.6469 |
| 0.0 | 72.01 | 15000 | 0.3752 | 11.4160 |
| 0.0 | 77.01 | 16000 | 0.3860 | 11.3411 |
| 0.0 | 82.01 | 17000 | 0.3943 | 11.3391 |
| 0.0 | 87.0 | 18000 | 0.4013 | 11.3532 |
| 0.0 | 92.0 | 19000 | 0.4063 | 11.3613 |
| 0.0 | 97.0 | 20000 | 0.4086 | 11.3512 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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