update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,82 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
datasets:
|
| 6 |
+
- emotion
|
| 7 |
+
metrics:
|
| 8 |
+
- f1
|
| 9 |
+
model-index:
|
| 10 |
+
- name: minilm-finetuned-emotion_nm
|
| 11 |
+
results:
|
| 12 |
+
- task:
|
| 13 |
+
name: Text Classification
|
| 14 |
+
type: text-classification
|
| 15 |
+
dataset:
|
| 16 |
+
name: emotion
|
| 17 |
+
type: emotion
|
| 18 |
+
args: default
|
| 19 |
+
metrics:
|
| 20 |
+
- name: F1
|
| 21 |
+
type: f1
|
| 22 |
+
value: 0.9322805793931607
|
| 23 |
+
---
|
| 24 |
+
|
| 25 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 26 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 27 |
+
|
| 28 |
+
# minilm-finetuned-emotion_nm
|
| 29 |
+
|
| 30 |
+
This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the emotion dataset.
|
| 31 |
+
It achieves the following results on the evaluation set:
|
| 32 |
+
- Loss: 0.1918
|
| 33 |
+
- F1: 0.9323
|
| 34 |
+
|
| 35 |
+
## Model description
|
| 36 |
+
|
| 37 |
+
More information needed
|
| 38 |
+
|
| 39 |
+
## Intended uses & limitations
|
| 40 |
+
|
| 41 |
+
More information needed
|
| 42 |
+
|
| 43 |
+
## Training and evaluation data
|
| 44 |
+
|
| 45 |
+
More information needed
|
| 46 |
+
|
| 47 |
+
## Training procedure
|
| 48 |
+
|
| 49 |
+
### Training hyperparameters
|
| 50 |
+
|
| 51 |
+
The following hyperparameters were used during training:
|
| 52 |
+
- learning_rate: 2e-05
|
| 53 |
+
- train_batch_size: 64
|
| 54 |
+
- eval_batch_size: 64
|
| 55 |
+
- seed: 42
|
| 56 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 57 |
+
- lr_scheduler_type: linear
|
| 58 |
+
- num_epochs: 10
|
| 59 |
+
- mixed_precision_training: Native AMP
|
| 60 |
+
|
| 61 |
+
### Training results
|
| 62 |
+
|
| 63 |
+
| Training Loss | Epoch | Step | Validation Loss | F1 |
|
| 64 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|
|
| 65 |
+
| 1.3627 | 1.0 | 250 | 1.0048 | 0.5936 |
|
| 66 |
+
| 0.8406 | 2.0 | 500 | 0.6477 | 0.8608 |
|
| 67 |
+
| 0.5344 | 3.0 | 750 | 0.4025 | 0.9099 |
|
| 68 |
+
| 0.3619 | 4.0 | 1000 | 0.3142 | 0.9188 |
|
| 69 |
+
| 0.274 | 5.0 | 1250 | 0.2489 | 0.9277 |
|
| 70 |
+
| 0.2225 | 6.0 | 1500 | 0.2320 | 0.9303 |
|
| 71 |
+
| 0.191 | 7.0 | 1750 | 0.2083 | 0.9298 |
|
| 72 |
+
| 0.1731 | 8.0 | 2000 | 0.1969 | 0.9334 |
|
| 73 |
+
| 0.1606 | 9.0 | 2250 | 0.1928 | 0.9362 |
|
| 74 |
+
| 0.1462 | 10.0 | 2500 | 0.1918 | 0.9323 |
|
| 75 |
+
|
| 76 |
+
|
| 77 |
+
### Framework versions
|
| 78 |
+
|
| 79 |
+
- Transformers 4.15.0
|
| 80 |
+
- Pytorch 1.10.0+cu111
|
| 81 |
+
- Datasets 1.17.0
|
| 82 |
+
- Tokenizers 0.10.3
|