File size: 2,060 Bytes
4e1be82 4669be6 57e4ded 4669be6 57e4ded 4669be6 57e4ded 4669be6 57e4ded 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 4e1be82 4669be6 |
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 |
---
language:
- fr
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: acoustic_model0_cv_17_fr_XLSR-53
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17
type: mozilla-foundation/common_voice_17_0
config: fr
split: test
args: fr
metrics:
- type: wer
value: 0.46428149722517414
name: Wer
---
<!-- 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. -->
# acoustic_model0_cv_17_fr_XLSR-53
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5171
- Wer: 0.4643
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.0475 | 2.084 | 400 | 2.9894 | 0.9949 |
| 1.2413 | 5.0767 | 800 | 0.6745 | 0.5958 |
| 0.5812 | 8.0693 | 1200 | 0.5171 | 0.4643 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|