File size: 2,250 Bytes
507bc50 bfa28e5 507bc50 bfa28e5 9b9abc1 507bc50 bfa28e5 9b9abc1 507bc50 bfa28e5 507bc50 bfa28e5 507bc50 9b9abc1 bfa28e5 507bc50 bfa28e5 9b9abc1 507bc50 bfa28e5 507bc50 |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-dutch-fast-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: nl
split: test
args: nl
metrics:
- name: Wer
type: wer
value: 0.39564262175027465
---
<!-- 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. -->
# wav2vec2-large-xls-r-300m-dutch-fast-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5291
- Wer: 0.3956
## 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: 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: 300
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.4755 | 0.34 | 200 | 2.9548 | 1.0000 |
| 2.1786 | 0.68 | 400 | 1.3052 | 0.8680 |
| 0.5853 | 1.02 | 600 | 0.8360 | 0.5886 |
| 0.3293 | 1.36 | 800 | 0.7055 | 0.5095 |
| 0.2581 | 1.7 | 1000 | 0.6768 | 0.4943 |
| 0.2023 | 2.04 | 1200 | 0.5974 | 0.4274 |
| 0.1336 | 2.37 | 1400 | 0.5872 | 0.4170 |
| 0.1186 | 2.71 | 1600 | 0.5291 | 0.3956 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|