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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: mms-1b-all-lg-CV-Fleurs_filtered-100hrs-v1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: lg_ug
split: test
args: lg_ug
metrics:
- name: Wer
type: wer
value: 0.4098153547133139
---
<!-- 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. -->
# mms-1b-all-lg-CV-Fleurs_filtered-100hrs-v1
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2897
- Wer: 0.4098
- Cer: 0.0743
## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 70
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.3203 | 1.0 | 7125 | 0.3178 | 0.4156 | 0.0762 |
| 0.2149 | 2.0 | 14250 | 0.3008 | 0.4194 | 0.0759 |
| 0.2093 | 3.0 | 21375 | 0.3015 | 0.4017 | 0.0743 |
| 0.2064 | 4.0 | 28500 | 0.3043 | 0.4114 | 0.0745 |
| 0.2042 | 5.0 | 35625 | 0.2955 | 0.4069 | 0.0753 |
| 0.2022 | 6.0 | 42750 | 0.3009 | 0.4088 | 0.0750 |
| 0.1989 | 7.0 | 49875 | 0.3088 | 0.4092 | 0.0756 |
| 0.1983 | 8.0 | 57000 | 0.2980 | 0.4081 | 0.0754 |
| 0.1969 | 9.0 | 64125 | 0.2951 | 0.4040 | 0.0741 |
| 0.1957 | 10.0 | 71250 | 0.2899 | 0.4039 | 0.0745 |
| 0.1945 | 11.0 | 78375 | 0.2896 | 0.4083 | 0.0744 |
| 0.1936 | 12.0 | 85500 | 0.2931 | 0.4038 | 0.0743 |
| 0.1929 | 13.0 | 92625 | 0.2897 | 0.4098 | 0.0743 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
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