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---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-MDBT-TCR_data-cl-cardiff_cl_only
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. -->
# scenario-MDBT-TCR_data-cl-cardiff_cl_only
This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6543
- Accuracy: 0.5131
- F1: 0.5145
## 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: 128
- seed: 66
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 2.17 | 250 | 1.4134 | 0.5069 | 0.5083 |
| 0.5524 | 4.35 | 500 | 1.9853 | 0.5208 | 0.5230 |
| 0.5524 | 6.52 | 750 | 2.5990 | 0.4853 | 0.4797 |
| 0.1315 | 8.7 | 1000 | 2.8603 | 0.4961 | 0.4954 |
| 0.1315 | 10.87 | 1250 | 3.1408 | 0.5093 | 0.5099 |
| 0.0497 | 13.04 | 1500 | 3.3859 | 0.5177 | 0.5190 |
| 0.0497 | 15.22 | 1750 | 3.9204 | 0.5039 | 0.5044 |
| 0.0219 | 17.39 | 2000 | 4.0747 | 0.5139 | 0.5160 |
| 0.0219 | 19.57 | 2250 | 4.3170 | 0.5139 | 0.5156 |
| 0.0133 | 21.74 | 2500 | 4.5924 | 0.5023 | 0.5020 |
| 0.0133 | 23.91 | 2750 | 4.6042 | 0.5100 | 0.5114 |
| 0.0046 | 26.09 | 3000 | 4.5407 | 0.5147 | 0.5163 |
| 0.0046 | 28.26 | 3250 | 4.6543 | 0.5131 | 0.5145 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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