metadata
license: apache-2.0
base_model: google/mt5-large
tags:
- generated_from_trainer
model-index:
- name: results
results: []
results
This model is a fine-tuned version of google/mt5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5622
- Loc: {'precision': 0.9222857142857143, 'recall': 0.9449648711943794, 'f1': 0.9334875650665124, 'number': 854}
- Org: {'precision': 0.8973561430793157, 'recall': 0.8876923076923077, 'f1': 0.8924980665119876, 'number': 650}
- Per: {'precision': 0.9014373716632443, 'recall': 0.9440860215053763, 'f1': 0.9222689075630252, 'number': 465}
- Overall Precision: 0.9092
- Overall Recall: 0.9259
- Overall F1: 0.9175
- Overall Accuracy: 0.9582
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Loc | Org | Per | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.1729 | 10.0 | 5000 | 0.4248 | {'precision': 0.9111361079865017, 'recall': 0.9484777517564403, 'f1': 0.9294320137693631, 'number': 854} | {'precision': 0.9027113237639554, 'recall': 0.8707692307692307, 'f1': 0.8864526233359435, 'number': 650} | {'precision': 0.9010309278350516, 'recall': 0.9397849462365592, 'f1': 0.92, 'number': 465} | 0.9060 | 0.9208 | 0.9134 | 0.9584 |
| 0.0068 | 20.0 | 10000 | 0.5622 | {'precision': 0.9222857142857143, 'recall': 0.9449648711943794, 'f1': 0.9334875650665124, 'number': 854} | {'precision': 0.8973561430793157, 'recall': 0.8876923076923077, 'f1': 0.8924980665119876, 'number': 650} | {'precision': 0.9014373716632443, 'recall': 0.9440860215053763, 'f1': 0.9222689075630252, 'number': 465} | 0.9092 | 0.9259 | 0.9175 | 0.9582 |
Framework versions
- Transformers 4.39.3
- Pytorch 1.11.0a0+17540c5
- Datasets 2.20.0
- Tokenizers 0.15.2