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End of training
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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distil_train_token_classification_new
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_train_token_classification_new
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5252
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8077
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.5713 | 1.0 | 7361 | 0.5417 | 0.0 | 0.0 | 0.0 | 0.7846 |
| 0.4646 | 2.0 | 14722 | 0.5028 | 0.0 | 0.0 | 0.0 | 0.8014 |
| 0.4084 | 3.0 | 22083 | 0.5115 | 0.0 | 0.0 | 0.0 | 0.8077 |
| 0.3601 | 4.0 | 29444 | 0.5252 | 0.0 | 0.0 | 0.0 | 0.8077 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0