File size: 2,999 Bytes
75cb0a3 |
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 |
---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-MARBERT-twitter-sentiment-Twitter
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. -->
# Improved-MARBERT-twitter-sentiment-Twitter
This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7706
- Accuracy: 0.86
## 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: 1e-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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5838 | 0.55 | 50 | 0.6058 | 0.71 |
| 0.3547 | 1.1 | 100 | 0.3887 | 0.83 |
| 0.2792 | 1.65 | 150 | 0.3479 | 0.85 |
| 0.1929 | 2.2 | 200 | 0.3596 | 0.87 |
| 0.1725 | 2.75 | 250 | 0.5874 | 0.8 |
| 0.1342 | 3.3 | 300 | 0.6560 | 0.81 |
| 0.1179 | 3.85 | 350 | 0.5146 | 0.85 |
| 0.079 | 4.4 | 400 | 0.6173 | 0.83 |
| 0.0928 | 4.95 | 450 | 0.7558 | 0.81 |
| 0.0425 | 5.49 | 500 | 1.0791 | 0.77 |
| 0.0609 | 6.04 | 550 | 0.7408 | 0.85 |
| 0.0328 | 6.59 | 600 | 0.8294 | 0.82 |
| 0.0531 | 7.14 | 650 | 0.6755 | 0.86 |
| 0.0342 | 7.69 | 700 | 0.6880 | 0.86 |
| 0.0263 | 8.24 | 750 | 0.7326 | 0.86 |
| 0.0147 | 8.79 | 800 | 0.8116 | 0.85 |
| 0.0169 | 9.34 | 850 | 0.8261 | 0.86 |
| 0.0118 | 9.89 | 900 | 0.7473 | 0.88 |
| 0.0087 | 10.44 | 950 | 0.7959 | 0.86 |
| 0.0051 | 10.99 | 1000 | 0.8585 | 0.85 |
| 0.0086 | 11.54 | 1050 | 0.8035 | 0.87 |
| 0.0076 | 12.09 | 1100 | 0.8838 | 0.84 |
| 0.0048 | 12.64 | 1150 | 0.8124 | 0.87 |
| 0.0095 | 13.19 | 1200 | 0.9262 | 0.85 |
| 0.0024 | 13.74 | 1250 | 0.8280 | 0.86 |
| 0.0109 | 14.29 | 1300 | 0.7895 | 0.87 |
| 0.0038 | 14.84 | 1350 | 0.7706 | 0.86 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
|