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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- recall
- precision
model-index:
- name: distil_bert_tuned_2
results: []
distil_bert_tuned_2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5698
- F1: 0.8253
- Accuracy: 0.7816
- Recall: 0.7088
- Precision: 0.2347
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Recall | Precision |
---|---|---|---|---|---|---|---|
0.5698 | 1.0 | 605 | 0.5390 | 0.8419 | 0.8063 | 0.6549 | 0.2502 |
0.5006 | 2.0 | 1210 | 0.5075 | 0.8052 | 0.7527 | 0.7599 | 0.2192 |
0.4526 | 3.0 | 1815 | 0.5698 | 0.8253 | 0.7816 | 0.7088 | 0.2347 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cpu
- Datasets 2.14.5
- Tokenizers 0.13.3