File size: 2,003 Bytes
e05c2f9 |
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 |
---
base_model: EleutherAI/pythia-14m
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: pythia-14m-imdb-sentiment-20240729_031828
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/lklab_kaist/pythia-14m-imdb-sentiment/runs/5cdsyszv)
# pythia-14m-imdb-sentiment-20240729_031828
This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingface.co/EleutherAI/pythia-14m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2606
- Accuracy: 0.891
- F1: 0.8925
- Precision: 0.8805
- Recall: 0.9048
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3715 | 1.0 | 782 | 0.3372 | 0.8540 | 0.8638 | 0.8095 | 0.926 |
| 0.234 | 2.0 | 1564 | 0.2606 | 0.891 | 0.8925 | 0.8805 | 0.9048 |
| 0.1667 | 3.0 | 2346 | 0.2820 | 0.8955 | 0.8951 | 0.8988 | 0.8914 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|