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---
library_name: transformers
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only55
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-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only55
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: 6.8361
- Accuracy: 0.3634
- F1: 0.3600
## 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: 32
- eval_batch_size: 32
- seed: 55
- 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 | 1.0870 | 250 | 1.4035 | 0.3627 | 0.3384 |
| 0.9258 | 2.1739 | 500 | 1.8269 | 0.3688 | 0.3652 |
| 0.9258 | 3.2609 | 750 | 2.2003 | 0.3696 | 0.3691 |
| 0.3143 | 4.3478 | 1000 | 3.2084 | 0.3850 | 0.3842 |
| 0.3143 | 5.4348 | 1250 | 3.4181 | 0.3719 | 0.3668 |
| 0.1172 | 6.5217 | 1500 | 3.9886 | 0.3688 | 0.3622 |
| 0.1172 | 7.6087 | 1750 | 4.2183 | 0.3650 | 0.3626 |
| 0.0592 | 8.6957 | 2000 | 4.6155 | 0.3665 | 0.3545 |
| 0.0592 | 9.7826 | 2250 | 4.7510 | 0.3727 | 0.3685 |
| 0.0394 | 10.8696 | 2500 | 5.1707 | 0.3688 | 0.3628 |
| 0.0394 | 11.9565 | 2750 | 5.0827 | 0.3681 | 0.3636 |
| 0.0238 | 13.0435 | 3000 | 5.5056 | 0.3665 | 0.3535 |
| 0.0238 | 14.1304 | 3250 | 5.3337 | 0.3704 | 0.3661 |
| 0.0171 | 15.2174 | 3500 | 5.7582 | 0.3735 | 0.3709 |
| 0.0171 | 16.3043 | 3750 | 5.9369 | 0.3665 | 0.3598 |
| 0.011 | 17.3913 | 4000 | 6.0815 | 0.3765 | 0.3719 |
| 0.011 | 18.4783 | 4250 | 6.1316 | 0.3819 | 0.3802 |
| 0.0043 | 19.5652 | 4500 | 6.3789 | 0.3727 | 0.3705 |
| 0.0043 | 20.6522 | 4750 | 6.4273 | 0.3673 | 0.3664 |
| 0.0064 | 21.7391 | 5000 | 6.3039 | 0.3758 | 0.3743 |
| 0.0064 | 22.8261 | 5250 | 6.5675 | 0.3619 | 0.3540 |
| 0.0031 | 23.9130 | 5500 | 6.5657 | 0.3688 | 0.3650 |
| 0.0031 | 25.0 | 5750 | 6.6382 | 0.3696 | 0.3666 |
| 0.0016 | 26.0870 | 6000 | 6.7416 | 0.3681 | 0.3643 |
| 0.0016 | 27.1739 | 6250 | 6.7141 | 0.3711 | 0.3677 |
| 0.0006 | 28.2609 | 6500 | 6.7905 | 0.3642 | 0.3600 |
| 0.0006 | 29.3478 | 6750 | 6.8361 | 0.3634 | 0.3600 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1
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