w2v2-bert-Wolof-5-hours-Google-Fleurs-dataset

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the fleurs dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.4897
• eval_wer: 0.4518
• eval_cer: 0.1503
• eval_runtime: 47.5107
• eval_samples_per_second: 7.809
• eval_steps_per_second: 0.989
• epoch: 39.02
• step: 1600

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: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 50

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu118
• Datasets 2.17.0
• Tokenizers 0.15.2