File size: 3,007 Bytes
ad129df 3e5f7b6 ad129df |
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 89 90 91 92 93 94 95 96 |
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-clinc_oos-distilled-clinc_oos
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
config: plus
split: validation
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9158064516129032
---
<!-- 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. -->
# bert-base-uncased-finetuned-clinc_oos-distilled-clinc_oos
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7724
- Accuracy: 0.9158
## Model Training Details
| Parameter | Value |
|----------------------|--------------------------------------------------|
| **Task** | text-classification |
| **Teacher Model** | bert-base-uncased-finetuned-clinc_oos |
| **Student Model** | distilbert-base-uncased |
| **Dataset Name** | clinc_oos |
| **Dataset Config** | plus |
| **Evaluation Dataset**| validation |
| **Batch Size** | 48 |
| **Number of Epochs** | 5 |
| **Learning Rate** | 0.00002 |
| **Alpha*** | 1 |
*alpha: (Total_loss = alpha * Loss_CE + (1-alpha) * Loss_KD)
## 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: 2e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 318 | 3.2762 | 0.7284 |
| 3.7824 | 2.0 | 636 | 1.8624 | 0.8358 |
| 3.7824 | 3.0 | 954 | 1.1512 | 0.8984 |
| 1.6858 | 4.0 | 1272 | 0.8540 | 0.9132 |
| 0.8983 | 5.0 | 1590 | 0.7724 | 0.9158 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|