File size: 3,434 Bytes
beddf47 b248ce5 a6d45a4 beddf47 b248ce5 beddf47 b248ce5 beddf47 b248ce5 beddf47 b248ce5 beddf47 b248ce5 |
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 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9409677419354838
- task:
type: text-classification
name: Text Classification
dataset:
name: clinc_oos
type: clinc_oos
config: small
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.8678181818181818
verified: true
- name: Precision Macro
type: precision
value: 0.8709070335541537
verified: true
- name: Precision Micro
type: precision
value: 0.8678181818181818
verified: true
- name: Precision Weighted
type: precision
value: 0.8873756372468106
verified: true
- name: Recall Macro
type: recall
value: 0.943794701986755
verified: true
- name: Recall Micro
type: recall
value: 0.8678181818181818
verified: true
- name: Recall Weighted
type: recall
value: 0.8678181818181818
verified: true
- name: F1 Macro
type: f1
value: 0.9010603026068839
verified: true
- name: F1 Micro
type: f1
value: 0.8678181818181818
verified: true
- name: F1 Weighted
type: f1
value: 0.8602590146783372
verified: true
- name: loss
type: loss
value: 0.8631454110145569
verified: true
---
<!-- 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: 0.1004
- Accuracy: 0.9410
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9037 | 1.0 | 318 | 0.5745 | 0.7326 |
| 0.4486 | 2.0 | 636 | 0.2866 | 0.8819 |
| 0.2537 | 3.0 | 954 | 0.1794 | 0.9210 |
| 0.1762 | 4.0 | 1272 | 0.1387 | 0.9294 |
| 0.1419 | 5.0 | 1590 | 0.1210 | 0.9358 |
| 0.1247 | 6.0 | 1908 | 0.1119 | 0.9413 |
| 0.1138 | 7.0 | 2226 | 0.1067 | 0.9387 |
| 0.1078 | 8.0 | 2544 | 0.1026 | 0.9423 |
| 0.1043 | 9.0 | 2862 | 0.1010 | 0.9413 |
| 0.102 | 10.0 | 3180 | 0.1004 | 0.9410 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.10.3
|