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---
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: []
---
<!-- 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. -->
# distil_bert_tuned_2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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