File size: 3,361 Bytes
7c8e91f |
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 |
---
license: apache-2.0
base_model: ltg/norbert3-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: norbert3-large-user-needs-v2
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. -->
# norbert3-large-user-needs-v2
This model is a fine-tuned version of [ltg/norbert3-large](https://huggingface.co/ltg/norbert3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1392
- Accuracy: 0.7067
- F1: 0.6946
- Precision: 0.6905
- Recall: 0.7067
## 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: 3e-05
- train_batch_size: 4
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log | 1.0 | 375 | 0.8059 | 0.6747 | 0.6472 | 0.6569 | 0.6747 |
| 0.9129 | 2.0 | 750 | 0.9030 | 0.6453 | 0.6142 | 0.5975 | 0.6453 |
| 0.7636 | 3.0 | 1125 | 0.7755 | 0.6667 | 0.6292 | 0.6250 | 0.6667 |
| 0.6003 | 4.0 | 1500 | 1.0267 | 0.6773 | 0.6591 | 0.6928 | 0.6773 |
| 0.6003 | 5.0 | 1875 | 1.9897 | 0.6267 | 0.6378 | 0.6526 | 0.6267 |
| 0.2905 | 6.0 | 2250 | 2.0507 | 0.704 | 0.6913 | 0.6879 | 0.704 |
| 0.0901 | 7.0 | 2625 | 2.7638 | 0.6853 | 0.6590 | 0.6863 | 0.6853 |
| 0.0365 | 8.0 | 3000 | 2.6138 | 0.696 | 0.6875 | 0.6907 | 0.696 |
| 0.0365 | 9.0 | 3375 | 3.0024 | 0.6667 | 0.6585 | 0.6543 | 0.6667 |
| 0.0162 | 10.0 | 3750 | 2.9416 | 0.6933 | 0.6829 | 0.6798 | 0.6933 |
| 0.0022 | 11.0 | 4125 | 3.2015 | 0.6827 | 0.6558 | 0.6790 | 0.6827 |
| 0.0114 | 12.0 | 4500 | 3.3133 | 0.6933 | 0.6694 | 0.6916 | 0.6933 |
| 0.0114 | 13.0 | 4875 | 3.2376 | 0.6773 | 0.6695 | 0.6647 | 0.6773 |
| 0.0042 | 14.0 | 5250 | 3.1392 | 0.7067 | 0.6946 | 0.6905 | 0.7067 |
| 0.0035 | 15.0 | 5625 | 3.2710 | 0.6907 | 0.6770 | 0.6705 | 0.6907 |
| 0.0045 | 16.0 | 6000 | 3.3476 | 0.6933 | 0.6847 | 0.6841 | 0.6933 |
| 0.0045 | 17.0 | 6375 | 3.2386 | 0.696 | 0.6904 | 0.6932 | 0.696 |
| 0.0065 | 18.0 | 6750 | 3.4263 | 0.6853 | 0.6700 | 0.6607 | 0.6853 |
| 0.0029 | 19.0 | 7125 | 3.4898 | 0.6827 | 0.6652 | 0.6579 | 0.6827 |
| 0.0013 | 20.0 | 7500 | 3.5103 | 0.68 | 0.6624 | 0.6554 | 0.68 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.15.2
|