End of training
Browse files
README.md
ADDED
|
@@ -0,0 +1,73 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: cardiffnlp/twitter-roberta-base-emotion
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
model-index:
|
| 8 |
+
- name: finetuned_roberta-base-on-IEMOCAP_4
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# finetuned_roberta-base-on-IEMOCAP_4
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-emotion](https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.5143
|
| 20 |
+
- Accuracy: 0.6867
|
| 21 |
+
|
| 22 |
+
## Model description
|
| 23 |
+
|
| 24 |
+
More information needed
|
| 25 |
+
|
| 26 |
+
## Intended uses & limitations
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Training and evaluation data
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training procedure
|
| 35 |
+
|
| 36 |
+
### Training hyperparameters
|
| 37 |
+
|
| 38 |
+
The following hyperparameters were used during training:
|
| 39 |
+
- learning_rate: 2e-05
|
| 40 |
+
- train_batch_size: 32
|
| 41 |
+
- eval_batch_size: 32
|
| 42 |
+
- seed: 42
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- num_epochs: 15
|
| 46 |
+
|
| 47 |
+
### Training results
|
| 48 |
+
|
| 49 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 50 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 51 |
+
| 0.8876 | 1.0 | 113 | 0.9530 | 0.6341 |
|
| 52 |
+
| 0.7153 | 2.0 | 226 | 0.8473 | 0.6807 |
|
| 53 |
+
| 0.5127 | 3.0 | 339 | 0.8841 | 0.6907 |
|
| 54 |
+
| 0.3844 | 4.0 | 452 | 0.9751 | 0.7062 |
|
| 55 |
+
| 0.3104 | 5.0 | 565 | 0.9363 | 0.7029 |
|
| 56 |
+
| 0.2374 | 6.0 | 678 | 1.1047 | 0.6896 |
|
| 57 |
+
| 0.2128 | 7.0 | 791 | 1.1239 | 0.7040 |
|
| 58 |
+
| 0.2104 | 8.0 | 904 | 1.1717 | 0.7129 |
|
| 59 |
+
| 0.1896 | 9.0 | 1017 | 1.1580 | 0.6973 |
|
| 60 |
+
| 0.1211 | 10.0 | 1130 | 1.2320 | 0.7029 |
|
| 61 |
+
| 0.1737 | 11.0 | 1243 | 1.3389 | 0.6973 |
|
| 62 |
+
| 0.1022 | 12.0 | 1356 | 1.3537 | 0.7062 |
|
| 63 |
+
| 0.0934 | 13.0 | 1469 | 1.3742 | 0.7140 |
|
| 64 |
+
| 0.0987 | 14.0 | 1582 | 1.4039 | 0.7151 |
|
| 65 |
+
| 0.1065 | 15.0 | 1695 | 1.4150 | 0.7173 |
|
| 66 |
+
|
| 67 |
+
|
| 68 |
+
### Framework versions
|
| 69 |
+
|
| 70 |
+
- Transformers 4.34.0
|
| 71 |
+
- Pytorch 2.0.1+cu118
|
| 72 |
+
- Datasets 2.14.5
|
| 73 |
+
- Tokenizers 0.14.1
|