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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_0.0001_0404_ES6_strict_tok1
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. -->
# tmvar_0.0001_0404_ES6_strict_tok1
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1472
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9561
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.3183 | 0.49 | 25 | 0.2344 | 0.0 | 0.0 | 0.0 | 0.9555 |
| 0.232 | 0.98 | 50 | 0.2467 | 0.0 | 0.0 | 0.0 | 0.9555 |
| 0.2357 | 1.47 | 75 | 0.2341 | 0.0 | 0.0 | 0.0 | 0.9555 |
| 0.2245 | 1.96 | 100 | 0.2373 | 0.0 | 0.0 | 0.0 | 0.9555 |
| 0.1778 | 2.45 | 125 | 0.1339 | 0.0 | 0.0 | 0.0 | 0.9555 |
| 0.137 | 2.94 | 150 | 0.1222 | 0.0 | 0.0 | 0.0 | 0.9582 |
| 0.1146 | 3.43 | 175 | 0.1339 | 0.0 | 0.0 | 0.0 | 0.9625 |
| 0.1215 | 3.92 | 200 | 0.1472 | 0.0 | 0.0 | 0.0 | 0.9561 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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