metadata
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: XLS-R-300M - Marathi
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_9_0
name: Common Voice 9
args: mr
metrics:
- type: wer
value: 23.841
name: Test WER
- name: Test CER
type: cer
value: 5.522
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - MR dataset. It achieves the following results on the evaluation set:
- Loss: 0.3642
- Wer: 0.4190
- Cer: 0.0946
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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 6124
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 3.5184 | 12.9 | 400 | 3.4210 | 1.0 | 1.0 |
| 2.3797 | 25.81 | 800 | 1.1068 | 0.8389 | 0.2584 |
| 1.5022 | 38.71 | 1200 | 0.5278 | 0.6280 | 0.1517 |
| 1.3181 | 51.61 | 1600 | 0.4254 | 0.5587 | 0.1297 |
| 1.2037 | 64.52 | 2000 | 0.3836 | 0.5143 | 0.1176 |
| 1.1245 | 77.42 | 2400 | 0.3643 | 0.4871 | 0.1111 |
| 1.0582 | 90.32 | 2800 | 0.3562 | 0.4676 | 0.1062 |
| 1.0027 | 103.23 | 3200 | 0.3530 | 0.4625 | 0.1058 |
| 0.9382 | 116.13 | 3600 | 0.3388 | 0.4442 | 0.1002 |
| 0.8915 | 129.03 | 4000 | 0.3430 | 0.4427 | 0.1000 |
| 0.853 | 141.94 | 4400 | 0.3536 | 0.4375 | 0.1000 |
| 0.8127 | 154.84 | 4800 | 0.3511 | 0.4344 | 0.0986 |
| 0.7861 | 167.74 | 5200 | 0.3595 | 0.4372 | 0.0993 |
| 0.7619 | 180.65 | 5600 | 0.3628 | 0.4316 | 0.0985 |
| 0.7537 | 193.55 | 6000 | 0.3633 | 0.4174 | 0.0943 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1