metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
- f1
model-index:
- name: scenario-MDBT-TCR_data-cl-massive_all_1_1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive
config: all_1.1
split: validation
args: all_1.1
metrics:
- name: Accuracy
type: accuracy
value: 0.8000036435845584
- name: F1
type: f1
value: 0.758305292124411
scenario-MDBT-TCR_data-cl-massive_all_1_1
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.3801
- Accuracy: 0.8000
- F1: 0.7583
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: 64
- seed: 66
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.489 | 0.56 | 5000 | 0.9200 | 0.7871 | 0.7332 |
| 0.2753 | 1.11 | 10000 | 1.0539 | 0.7885 | 0.7364 |
| 0.2348 | 1.67 | 15000 | 1.0362 | 0.7891 | 0.7431 |
| 0.1648 | 2.22 | 20000 | 1.1925 | 0.7867 | 0.7535 |
| 0.1481 | 2.78 | 25000 | 1.1608 | 0.7920 | 0.7513 |
| 0.1074 | 3.33 | 30000 | 1.3151 | 0.7966 | 0.7513 |
| 0.0942 | 3.89 | 35000 | 1.3274 | 0.7952 | 0.7523 |
| 0.0684 | 4.45 | 40000 | 1.3801 | 0.8000 | 0.7583 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3