Hugging Face's logo

doyoungkim
/
bert-base-uncased-finetuned-sst2

Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
3
doyoungkim commited on
Commit
69887b1
•
1 Parent(s): 46eb884

add model

Browse files
Files changed (3) hide show
  1. README.md +12 -12
  2. pytorch_model.bin +2 -2
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ model_index:
16
  metric:
17
  name: Accuracy
18
  type: accuracy
19
- value: 0.9220183486238532
20
  ---
21
 
22
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -26,8 +26,8 @@ should probably proofread and complete it, then remove this comment. -->
26
 
27
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
28
  It achieves the following results on the evaluation set:
29
- - Loss: 0.3912
30
- - Accuracy: 0.9220
31
 
32
  ## Model description
33
 
@@ -47,8 +47,8 @@ More information needed
47
 
48
  The following hyperparameters were used during training:
49
  - learning_rate: 2e-05
50
- - train_batch_size: 16
51
- - eval_batch_size: 16
52
  - seed: 42
53
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
54
  - lr_scheduler_type: linear
@@ -58,16 +58,16 @@ The following hyperparameters were used during training:
58
 
59
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
60
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
61
- | 0.4005 | 1.0 | 4210 | 0.4058 | 0.9025 |
62
- | 0.3707 | 2.0 | 8420 | 0.4141 | 0.8968 |
63
- | 0.3554 | 3.0 | 12630 | 0.3978 | 0.9151 |
64
- | 0.3551 | 4.0 | 16840 | 0.3912 | 0.9220 |
65
- | 0.353 | 5.0 | 21050 | 0.3930 | 0.9209 |
66
 
67
 
68
  ### Framework versions
69
 
70
  - Transformers 4.9.1
71
- - Pytorch 1.9.0+cu102
72
  - Datasets 1.11.0
73
- - Tokenizers 0.10.3
 
16
  metric:
17
  name: Accuracy
18
  type: accuracy
19
+ value: 0.9231651376146789
20
  ---
21
 
22
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
26
 
27
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
28
  It achieves the following results on the evaluation set:
29
+ - Loss: 0.3905
30
+ - Accuracy: 0.9232
31
 
32
  ## Model description
33
 
 
47
 
48
  The following hyperparameters were used during training:
49
  - learning_rate: 2e-05
50
+ - train_batch_size: 32
51
+ - eval_batch_size: 32
52
  - seed: 42
53
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
54
  - lr_scheduler_type: linear
 
58
 
59
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
60
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
61
+ | 0.3915 | 1.0 | 2105 | 0.3969 | 0.9140 |
62
+ | 0.3667 | 2.0 | 4210 | 0.3936 | 0.9174 |
63
+ | 0.3609 | 3.0 | 6315 | 0.3913 | 0.9209 |
64
+ | 0.3518 | 4.0 | 8420 | 0.3905 | 0.9232 |
65
+ | 0.3467 | 5.0 | 10525 | 0.3923 | 0.9186 |
66
 
67
 
68
  ### Framework versions
69
 
70
  - Transformers 4.9.1
71
+ - Pytorch 1.8.1
72
  - Datasets 1.11.0
73
+ - Tokenizers 0.10.1
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f3e1b12c48262deb02b0778841a36e23aece59f0390ae2d5cf14a97e1ac4ee1a
3
- size 438019245
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:efa5902e51688fb049d08a5ab2be061e3aa6537e05d8bc77f07327de04aafda5
3
+ size 438024457
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:96d8d04ca494e7b49419da45278a17f6635505add6ff0a074de77f676355fa5d
3
  size 2671
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a9895d89c436c696a54984d0c7d12e9ebe7a8d284b2629d04c469494386e7fc
3
  size 2671