File size: 2,237 Bytes
18f0cfd d6188f2 18f0cfd d6188f2 18f0cfd d6188f2 18f0cfd d6188f2 18f0cfd |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- type: accuracy
value: 0.9464516129032258
name: Accuracy
---
<!-- 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. -->
# distilbert-base-uncased-distilled-clinc
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: 0.3038
- Accuracy: 0.9465
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 318 | 2.8460 | 0.7506 |
| 3.322 | 2.0 | 636 | 1.4301 | 0.8532 |
| 3.322 | 3.0 | 954 | 0.7377 | 0.9152 |
| 1.2296 | 4.0 | 1272 | 0.4784 | 0.9316 |
| 0.449 | 5.0 | 1590 | 0.3730 | 0.9390 |
| 0.449 | 6.0 | 1908 | 0.3367 | 0.9429 |
| 0.2424 | 7.0 | 2226 | 0.3163 | 0.9468 |
| 0.1741 | 8.0 | 2544 | 0.3074 | 0.9452 |
| 0.1741 | 9.0 | 2862 | 0.3054 | 0.9458 |
| 0.1501 | 10.0 | 3180 | 0.3038 | 0.9465 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
|