File size: 1,767 Bytes
fe50eb0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
---
base_model: gpt2
library_name: peft
license: mit
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: gpt2-sst2-sentiment-classifier-lora
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-sst2-sentiment-classifier-lora
This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2636
- Accuracy: 0.9083
- F1: 0.9111
- Precision: 0.8991
- Recall: 0.9234
## 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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3138 | 1.0 | 4210 | 0.2550 | 0.9014 | 0.9034 | 0.9013 | 0.9054 |
| 0.2597 | 2.0 | 8420 | 0.2666 | 0.9014 | 0.9061 | 0.8792 | 0.9347 |
| 0.2436 | 3.0 | 12630 | 0.2636 | 0.9083 | 0.9111 | 0.8991 | 0.9234 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1 |