File size: 3,126 Bytes
957ee5d 13f7f02 957ee5d 13f7f02 957ee5d 13f7f02 957ee5d 13f7f02 957ee5d 13f7f02 957ee5d 13f7f02 957ee5d 13f7f02 957ee5d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
---
language:
- pt
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 Portuguese
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 pt
type: mozilla-foundation/common_voice_13_0
config: pt
split: test
args: pt
metrics:
- name: Wer
type: wer
value: 6.450234942332337
---
<!-- 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 Portuguese
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 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4115
- Wer: 6.4502
## 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0424 | 3.53 | 1000 | 0.1879 | 5.9886 |
| 0.0093 | 7.05 | 2000 | 0.2493 | 6.2744 |
| 0.0049 | 10.58 | 3000 | 0.2656 | 6.3500 |
| 0.0031 | 14.11 | 4000 | 0.2850 | 6.4256 |
| 0.0029 | 17.64 | 5000 | 0.3013 | 6.5833 |
| 0.0053 | 21.16 | 6000 | 0.2810 | 6.7969 |
| 0.0033 | 24.69 | 7000 | 0.3072 | 6.8905 |
| 0.0007 | 28.22 | 8000 | 0.3210 | 6.7312 |
| 0.0021 | 31.75 | 9000 | 0.3311 | 6.9924 |
| 0.0006 | 35.27 | 10000 | 0.3188 | 6.7295 |
| 0.0002 | 38.8 | 11000 | 0.3336 | 6.6589 |
| 0.0004 | 42.33 | 12000 | 0.3465 | 6.9086 |
| 0.0004 | 45.86 | 13000 | 0.3340 | 6.9924 |
| 0.0001 | 49.38 | 14000 | 0.3607 | 6.8199 |
| 0.0001 | 52.91 | 15000 | 0.3779 | 6.6112 |
| 0.0 | 56.44 | 16000 | 0.3884 | 6.5505 |
| 0.0 | 59.96 | 17000 | 0.3966 | 6.4897 |
| 0.0 | 63.49 | 18000 | 0.4039 | 6.4650 |
| 0.0 | 67.02 | 19000 | 0.4091 | 6.4486 |
| 0.0 | 70.55 | 20000 | 0.4115 | 6.4502 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.15.1
|