File size: 5,933 Bytes
40d2b6c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 6db4a91 1ea5e0c 40d2b6c |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model_index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metric:
name: F1
type: f1
value: 0.9327347950817506
model-index:
- name: jsoutherland/distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
config: default
split: test
metrics:
- type: accuracy
value: 0.925
name: Accuracy
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjczZjBkOGFlNWRiZTg3NTA1MDc2NDhhZmExNzlhYmJjYjRlODgxNTUwZDI1NDUzMjViYTU1NTE1YjY0NzhhMCIsInZlcnNpb24iOjF9.V2oCF0Y-F41cLXjFU1GpuBjI3F4D8tL5H1iizFIxn6AYC5n-3jUOYo80QBs4EmQZP449nQugdHk5-iFSWF4iAQ
- type: precision
value: 0.8954208010579672
name: Precision Macro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2U1YjZlNmNlZGRmYThjMWE5MGM3ZDcwNjVmZjlmMWU1MjAzOGUyMzgzNmVmYzYyMmUxNmFkYzdlYWE5ZGU5NyIsInZlcnNpb24iOjF9.LoFXbY2rcvQ92c5qpmxW_EfIDlDKh3I6eSrRBVWw0oZxjKzsapxeIGMdkOA6ZinQKtlWP0fQcA56jEhIjiJICA
- type: precision
value: 0.925
name: Precision Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjk5ZDUzNDFmMzBmZDNmNjk5N2Y1YTQzNTE2MjM3MGQ5YWM1Zjk0MmU3YzU3MmU0ODJlNjZlMjg1MWE5NjAwNyIsInZlcnNpb24iOjF9.PFWMLKFjyJSeQqKEU_HbGbI0An9bXUV13v5gNFldpmO8q08Jg_T-x5YK-NmEuQ4G56JdpKgTAAmivlhYWxRKDw
- type: precision
value: 0.9256567173431012
name: Precision Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGY2MTE5OGUyZGM1YWJkOGYwZjExYmE1OGUyODI3NzQyZTU1ZGM4ZDgyMTBiZWYyZTFhNzJkOWM1MjI2ZGQwYyIsInZlcnNpb24iOjF9.nNG5SP3x7xXkpP9j8H58i58CQhkObYnR6I3N65L-GJGypY86dIukYWN_5JIEeBBTb6sxGq5hed6lNYqFNd2RBw
- type: recall
value: 0.8711059962680445
name: Recall Macro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTI0ZGE1MTZmOWU1MWE3ZjI5NGFiMTg3Y2Q2YzY4MjMwOTBjODFmMTllNWI5ZGVjNTViY2NiNmNiZGQ4NjhhYiIsInZlcnNpb24iOjF9.jVQbGWGGFAwz4HXOXEd5LMhd5ayC4lORtnfexVXW-WyDpsCzHrVMHShwX4g8RiRzMpReYB_0nGniv0p9egNGDA
- type: recall
value: 0.925
name: Recall Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWYxMGY3MDIzMTdiNzU0MzBhNThiYjA5OTkxNjFjYjIzZmVlZjA0YTRlZDhiYzhmMDAwMTQ5NjhmYWNjY2ZjNSIsInZlcnNpb24iOjF9.Pzn0p18B43AaofOnT9ZPkTG8qwwhxUYhG9xPi35tJR7oHUsfzUtGVsWSd0BQd49W45CzUU5kUdaeZZFmSgqfAg
- type: recall
value: 0.925
name: Recall Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzA3Y2I0NzBjYTExODBiZjc3NDZhOTA5MzI4NjAyYWE0ZjA3NTc5ZjNiNmEzNzdmNDljZDJiOTcwNThlNTE4MiIsInZlcnNpb24iOjF9.gPDirWMiSMD6FMc_Ruz5Td7gBm4dY0EFRjcEPuzryQEMc7FTviQ5QCrnpQDJRAanlrASYqTtiUEfHtUfYURHAg
- type: f1
value: 0.8794773714607985
name: F1 Macro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTM5NjZmNjI5NjE0MTdlZTQ0YjkxMGQ4Y2QzZTBiYzc0NTg1YzYxM2UxYTI0NTBlMWU3OTE0ZjEyNWI1NmJiMyIsInZlcnNpb24iOjF9.vyL-0gLHzckauTA_xJB_2YplAJEsHnrxft6jQthjRRf3o_-jgHMe6bH2vOGfYR__XwdVUJOPadNRQVkq--b0AQ
- type: f1
value: 0.925
name: F1 Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmU5NWRjMGU4NTdhOTZiMTgyMjMyMTQxNDliNGNkNDUxNDJmMjZkNTgyYWFkY2ZiMDBkOWY2ODE5Zjg4YzgyNSIsInZlcnNpb24iOjF9.xX1RzQgLPX2oSwbqklGpxM7I0NZi1B7TdFfo7KJ0KmGiyOxc9zOjgm7PlBUFq0_lOWyJa4BQUXLiXmFTUc-CDQ
- type: f1
value: 0.9244781949774824
name: F1 Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWVhMTE3ZWFhYTJmYzQ0OGY4YmY3MzZmNzk0YmU5NGE0Zjg2ZWJhYWE2MTAzMDk3MWRlMWM0NGFhNzg3MGU4YiIsInZlcnNpb24iOjF9.NZIQRvbFt0SujrtCG9-saaLiuyO90ZFIR_uKuSzxAmfsV8eP2SBl7FHW5_L3BS2OGj5JCVjqlZVRg1OjBOm5DQ
- type: loss
value: 0.17752596735954285
name: loss
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzEwMzc3MWViYTVlNjg3MmMyYjIzNDUzNjJkNGYyYTZmYzM4MDMyYzhkZDNiMDg4YzJlMjcwNmY4ZmJhMDcwYiIsInZlcnNpb24iOjF9.st-K9FBxyhOPF_u2fNcooLyT7R8IPZaalo85UurBB98fRSe2k_RzvhS9YuwxqflclJ9l66pZgcAv-hkANv10DA
---
<!-- 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-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1649
- Accuracy: 0.9325
- F1: 0.9327
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 250 | 0.2838 | 0.9065 | 0.9036 |
| No log | 2.0 | 500 | 0.1795 | 0.9255 | 0.9255 |
| No log | 3.0 | 750 | 0.1649 | 0.9325 | 0.9327 |
### Framework versions
- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 2.1.0
- Tokenizers 0.10.3
|