File size: 3,537 Bytes
8d9521d |
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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
---
license: apache-2.0
base_model: raffel-22/emotion_classification_2
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_classification_2_continue
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.725
---
<!-- 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. -->
# emotion_classification_2_continue
This model is a fine-tuned version of [raffel-22/emotion_classification_2](https://huggingface.co/raffel-22/emotion_classification_2) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8978
- Accuracy: 0.725
## 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: 4e-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
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 20 | 0.9714 | 0.7063 |
| No log | 2.0 | 40 | 0.9432 | 0.7188 |
| No log | 3.0 | 60 | 0.9633 | 0.7 |
| No log | 4.0 | 80 | 0.9322 | 0.7375 |
| No log | 5.0 | 100 | 0.8530 | 0.7063 |
| No log | 6.0 | 120 | 0.9063 | 0.7063 |
| No log | 7.0 | 140 | 0.8451 | 0.7125 |
| No log | 8.0 | 160 | 0.9672 | 0.6375 |
| No log | 9.0 | 180 | 0.9036 | 0.6937 |
| No log | 10.0 | 200 | 0.9261 | 0.6562 |
| No log | 11.0 | 220 | 0.8963 | 0.6937 |
| No log | 12.0 | 240 | 0.8852 | 0.7188 |
| No log | 13.0 | 260 | 0.8728 | 0.7063 |
| No log | 14.0 | 280 | 0.9559 | 0.6875 |
| No log | 15.0 | 300 | 0.9352 | 0.65 |
| No log | 16.0 | 320 | 0.8638 | 0.7 |
| No log | 17.0 | 340 | 0.9156 | 0.7 |
| No log | 18.0 | 360 | 1.0299 | 0.6687 |
| No log | 19.0 | 380 | 0.8983 | 0.675 |
| No log | 20.0 | 400 | 0.8858 | 0.7063 |
| No log | 21.0 | 420 | 0.9699 | 0.6937 |
| No log | 22.0 | 440 | 1.0603 | 0.625 |
| No log | 23.0 | 460 | 1.0404 | 0.6312 |
| No log | 24.0 | 480 | 0.8838 | 0.6937 |
| 0.4269 | 25.0 | 500 | 0.9280 | 0.6937 |
| 0.4269 | 26.0 | 520 | 0.9456 | 0.6937 |
| 0.4269 | 27.0 | 540 | 0.9640 | 0.6937 |
| 0.4269 | 28.0 | 560 | 0.9865 | 0.6937 |
| 0.4269 | 29.0 | 580 | 0.8900 | 0.7188 |
| 0.4269 | 30.0 | 600 | 0.9408 | 0.7063 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|