WAXAL Mlg Asr W2v Bert 2.0

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: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10

Training results

Framework versions

• Transformers 5.12.1
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2

--- library_name: transformers license: mit base_model: facebook/w2v-bert-2.0 tags: - generated_from_trainer model-index: - name: WAXAL-mlg_asr-w2v-bert-2.0 results: [] --- <!-- 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. --> # WAXAL-mlg_asr-w2v-bert-2.0 This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8135 - Cer: 0.2007 ## 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: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:------:|:----:|:---------------:|:------:| | 3.6449 | 1.7544 | 300 | 0.8086 | 0.2391 | | 0.5700 | 3.5088 | 600 | 0.7955 | 0.2231 | | 0.3980 | 5.2632 | 900 | 0.7420 | 0.2109 | | 0.2475 | 7.0175 | 1200 | 0.7624 | 0.2048 | | 0.1611 | 8.7719 | 1500 | 0.8076 | 0.2016 | | 0.1611 | 10.0 | 1710 | 0.8135 | 0.2007 | ### Framework versions - Transformers 5.12.1 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2