README.md

metadata

license: mit
base_model: facebook/w2v-bert-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results
    results: []

results

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

• Loss: 1.6006
• Accuracy: 0.5153
• F1 Score Class 0: 0.0
• F1 Score Class 1: 0.0
• F1 Score Class 2: 0.0
• F1 Score Class 3: 0.0
• F1 Score Class 4: 0.0
• F1 Score Class 5: 0.0
• F1 Score Class 6: 0.0
• F1 Score Class 7: 0.6801
• F1 Score Class 8: 0.0

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Score Class 0	F1 Score Class 1	F1 Score Class 2	F1 Score Class 3	F1 Score Class 4	F1 Score Class 5	F1 Score Class 6	F1 Score Class 7	F1 Score Class 8
1.506	1.0	533	1.6378	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.4754	2.0	1066	1.6081	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.5661	3.0	1599	1.6086	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.5656	4.0	2132	1.6012	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.6768	5.0	2665	1.6281	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.6289	6.0	3198	1.6011	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.4727	7.0	3731	1.6015	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.5386	8.0	4264	1.6054	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.5436	9.0	4797	1.6020	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0
1.4974	10.0	5330	1.6006	0.5153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.6801	0.0

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1