File size: 2,112 Bytes
159df15 2b7bf57 159df15 be104e5 2b7bf57 159df15 2b7bf57 159df15 be104e5 d37b25a 2b7bf57 be104e5 2b7bf57 be104e5 2b7bf57 159df15 8a63344 159df15 1ecb245 |
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 |
---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- nlu
- text-classification
datasets:
- AmazonScience/massive
metrics:
- accuracy
- f1
base_model: bert-base-uncased
model-index:
- name: bert-base-uncased-amazon-massive-intent
results:
- task:
type: intent-classification
name: intent-classification
dataset:
name: MASSIVE
type: AmazonScience/massive
split: test
metrics:
- type: f1
value: 0.8903
name: F1
---
<!-- 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-amazon-massive-intent
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on
[Amazon Massive](https://huggingface.co./datasets/AmazonScience/massive) dataset (only en-US subset).
It achieves the following results on the evaluation set:
- Loss: 0.4897
- Accuracy: 0.8903
- F1: 0.8903
## 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: 16
- eval_batch_size: 16
- 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 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.5862 | 1.0 | 720 | 1.0160 | 0.8096 | 0.8096 |
| 1.0591 | 2.0 | 1440 | 0.6003 | 0.8716 | 0.8716 |
| 0.4151 | 3.0 | 2160 | 0.5113 | 0.8859 | 0.8859 |
| 0.3028 | 4.0 | 2880 | 0.5030 | 0.8883 | 0.8883 |
| 0.1852 | 5.0 | 3600 | 0.4897 | 0.8903 | 0.8903 |
### Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1 |