File size: 2,308 Bytes
7773fb6 ffee101 7773fb6 ffee101 7773fb6 ffee101 7773fb6 ffee101 7773fb6 ffee101 7773fb6 ffee101 7773fb6 ffee101 7773fb6 2d82c21 7773fb6 |
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 |
---
library_name: transformers
language:
- gn
license: apache-2.0
base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Common Voice 16
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16
type: mozilla-foundation/common_voice_16_1
config: gn
split: None
args: gn
metrics:
- name: Wer
type: wer
value: 39.84010659560293
---
<!-- 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. -->
# Common Voice 16
This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2438
- Wer: 39.8401
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 3000
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.2579 | 0.4955 | 500 | 0.3710 | 53.4310 |
| 0.919 | 0.9911 | 1000 | 0.3295 | 49.9001 |
| 0.746 | 1.4866 | 1500 | 0.2902 | 45.1033 |
| 0.6767 | 1.9822 | 2000 | 0.2674 | 43.3711 |
| 0.574 | 2.4777 | 2500 | 0.2677 | 42.5716 |
| 0.5485 | 2.9732 | 3000 | 0.2438 | 39.8401 |
### Framework versions
- Transformers 4.44.1
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|