metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: pixel-base-finetune-sent
results: []
pixel-base-finetune-sent
This model is a fine-tuned version of Team-PIXEL/pixel-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.4999
- Accuracy: 0.3702
- Qwk: 0.6030
- Mae: 1.9328
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 50000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Qwk | Mae |
|---|---|---|---|---|---|---|
| 2.0132 | 0.58 | 1000 | 2.0384 | 0.2788 | 0.5991 | 2.0788 |
| 1.9246 | 1.17 | 2000 | 1.9957 | 0.2979 | 0.6192 | 2.0294 |
| 1.9128 | 1.75 | 3000 | 1.9440 | 0.3218 | 0.5979 | 2.0585 |
| 1.792 | 2.33 | 4000 | 1.9316 | 0.3271 | 0.6068 | 1.9224 |
| 1.7771 | 2.92 | 5000 | 1.8539 | 0.3557 | 0.6218 | 1.8866 |
| 1.6715 | 3.5 | 6000 | 1.8448 | 0.3665 | 0.6286 | 1.8692 |
| 1.5602 | 4.08 | 7000 | 1.8855 | 0.3692 | 0.5773 | 2.0124 |
| 1.5562 | 4.67 | 8000 | 1.8120 | 0.3837 | 0.6033 | 1.8889 |
| 1.4078 | 5.25 | 9000 | 1.8713 | 0.3884 | 0.6243 | 1.8740 |
| 1.4296 | 5.83 | 10000 | 1.8595 | 0.3865 | 0.6071 | 1.9174 |
| 1.269 | 6.42 | 11000 | 1.9294 | 0.3989 | 0.6260 | 1.8328 |
| 1.3173 | 7.0 | 12000 | 1.9485 | 0.3796 | 0.6218 | 1.9100 |
| 1.1227 | 7.58 | 13000 | 2.0674 | 0.3893 | 0.6181 | 1.8724 |
| 0.8926 | 8.17 | 14000 | 2.3098 | 0.3819 | 0.6120 | 1.8919 |
| 0.9693 | 8.75 | 15000 | 2.2659 | 0.3862 | 0.6195 | 1.8196 |
| 0.7348 | 9.33 | 16000 | 2.5195 | 0.3828 | 0.6031 | 1.9008 |
| 0.8165 | 9.92 | 17000 | 2.4748 | 0.3824 | 0.6125 | 1.8863 |
| 0.6071 | 10.5 | 18000 | 2.7954 | 0.3718 | 0.6138 | 1.8930 |
| 0.4994 | 11.09 | 19000 | 3.0574 | 0.3681 | 0.6113 | 1.9193 |
| 0.5026 | 11.67 | 20000 | 3.0452 | 0.3550 | 0.5989 | 1.9430 |
| 0.3619 | 12.25 | 21000 | 3.2941 | 0.3576 | 0.5921 | 1.9748 |
| 0.3928 | 12.84 | 22000 | 3.4092 | 0.3561 | 0.6070 | 1.9112 |
| 0.2999 | 13.42 | 23000 | 3.5744 | 0.3661 | 0.6001 | 1.9334 |
| 0.3142 | 14.0 | 24000 | 3.5801 | 0.3703 | 0.6258 | 1.8979 |
| 0.2513 | 14.59 | 25000 | 3.7402 | 0.3699 | 0.6177 | 1.9004 |
| 0.1896 | 15.17 | 26000 | 3.9153 | 0.3752 | 0.6147 | 1.8882 |
| 0.2204 | 15.75 | 27000 | 3.9247 | 0.3747 | 0.6165 | 1.9239 |
| 0.1522 | 16.34 | 28000 | 4.1680 | 0.3703 | 0.5994 | 1.9439 |
| 0.1844 | 16.92 | 29000 | 4.2140 | 0.3752 | 0.6022 | 1.9122 |
| 0.1331 | 17.5 | 30000 | 4.4904 | 0.3736 | 0.5998 | 1.8850 |
| 0.1141 | 18.09 | 31000 | 4.4999 | 0.3702 | 0.6030 | 1.9328 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.5.1
- Datasets 3.6.0
- Tokenizers 0.21.1