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---
tags:
- generated_from_trainer
model-index:
- name: gpt2-gpt2-mc-weight0.25-epoch15-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. -->
# gpt2-gpt2-mc-weight0.25-epoch15-new
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7276
- Cls loss: 3.0579
- Lm loss: 3.9626
- Cls Accuracy: 0.6110
- Cls F1: 0.6054
- Cls Precision: 0.6054
- Cls Recall: 0.6110
- Perplexity: 52.59
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
| 4.674 | 1.0 | 3470 | 4.4372 | 1.5961 | 4.0380 | 0.5487 | 0.5279 | 0.5643 | 0.5487 | 56.71 |
| 4.3809 | 2.0 | 6940 | 4.3629 | 1.4483 | 4.0006 | 0.6023 | 0.5950 | 0.6174 | 0.6023 | 54.63 |
| 4.2522 | 3.0 | 10410 | 4.3721 | 1.5476 | 3.9849 | 0.6012 | 0.5981 | 0.6186 | 0.6012 | 53.78 |
| 4.1478 | 4.0 | 13880 | 4.3892 | 1.6429 | 3.9782 | 0.6081 | 0.6019 | 0.6128 | 0.6081 | 53.42 |
| 4.0491 | 5.0 | 17350 | 4.4182 | 1.8093 | 3.9656 | 0.6156 | 0.6091 | 0.6163 | 0.6156 | 52.75 |
| 3.9624 | 6.0 | 20820 | 4.4757 | 2.0348 | 3.9666 | 0.6121 | 0.6048 | 0.6189 | 0.6121 | 52.81 |
| 3.8954 | 7.0 | 24290 | 4.4969 | 2.1327 | 3.9634 | 0.6092 | 0.6028 | 0.6087 | 0.6092 | 52.64 |
| 3.846 | 8.0 | 27760 | 4.5632 | 2.4063 | 3.9613 | 0.6017 | 0.5972 | 0.6014 | 0.6017 | 52.52 |
| 3.8036 | 9.0 | 31230 | 4.6068 | 2.5888 | 3.9592 | 0.6052 | 0.5988 | 0.6026 | 0.6052 | 52.41 |
| 3.7724 | 10.0 | 34700 | 4.6175 | 2.6197 | 3.9621 | 0.6052 | 0.6006 | 0.6009 | 0.6052 | 52.57 |
| 3.7484 | 11.0 | 38170 | 4.6745 | 2.8470 | 3.9622 | 0.6046 | 0.5996 | 0.6034 | 0.6046 | 52.57 |
| 3.7291 | 12.0 | 41640 | 4.6854 | 2.8950 | 3.9611 | 0.6110 | 0.6056 | 0.6049 | 0.6110 | 52.52 |
| 3.7148 | 13.0 | 45110 | 4.7103 | 2.9919 | 3.9618 | 0.6063 | 0.6002 | 0.6029 | 0.6063 | 52.55 |
| 3.703 | 14.0 | 48580 | 4.7226 | 3.0417 | 3.9616 | 0.6081 | 0.6027 | 0.6021 | 0.6081 | 52.54 |
| 3.6968 | 15.0 | 52050 | 4.7276 | 3.0579 | 3.9626 | 0.6110 | 0.6054 | 0.6054 | 0.6110 | 52.59 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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