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End of training

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  1. README.md +10 -95
  2. config.json +2 -2
  3. pytorch_model.bin +2 -2
  4. tokenizer.json +2 -1
  5. tokenizer_config.json +826 -0
  6. training_args.bin +2 -2
README.md CHANGED
@@ -5,24 +5,9 @@ tags:
5
  - generated_from_trainer
6
  datasets:
7
  - glue
8
- metrics:
9
- - accuracy
10
  model-index:
11
  - name: t5-base_cola_dense
12
- results:
13
- - task:
14
- name: Text Classification
15
- type: text-classification
16
- dataset:
17
- name: glue
18
- type: glue
19
- config: cola
20
- split: validation
21
- args: cola
22
- metrics:
23
- - name: Accuracy
24
- type: accuracy
25
- value: 0.8370086289549377
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
32
 
33
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 0.4482
36
- - Accuracy: 0.8370
 
 
 
 
37
 
38
  ## Model description
39
 
@@ -56,90 +45,16 @@ The following hyperparameters were used during training:
56
  - train_batch_size: 32
57
  - eval_batch_size: 64
58
  - seed: 42
59
- - distributed_type: multi-GPU
60
  - gradient_accumulation_steps: 2
61
  - total_train_batch_size: 64
62
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
63
  - lr_scheduler_type: linear
64
  - lr_scheduler_warmup_steps: 200
65
- - num_epochs: 5
66
-
67
- ### Training results
68
-
69
- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
70
- |:-------------:|:-----:|:----:|:---------------:|:--------:|
71
- | 0.6484 | 0.07 | 10 | 0.6254 | 0.6913 |
72
- | 0.6188 | 0.15 | 20 | 0.6181 | 0.6913 |
73
- | 0.625 | 0.22 | 30 | 0.6137 | 0.6913 |
74
- | 0.5744 | 0.3 | 40 | 0.6063 | 0.6913 |
75
- | 0.6055 | 0.37 | 50 | 0.5963 | 0.6913 |
76
- | 0.5723 | 0.45 | 60 | 0.5788 | 0.6913 |
77
- | 0.5777 | 0.52 | 70 | 0.5527 | 0.6913 |
78
- | 0.5332 | 0.6 | 80 | 0.5117 | 0.7354 |
79
- | 0.4662 | 0.67 | 90 | 0.5060 | 0.7843 |
80
- | 0.4936 | 0.75 | 100 | 0.4717 | 0.7929 |
81
- | 0.4898 | 0.82 | 110 | 0.5304 | 0.8015 |
82
- | 0.4844 | 0.9 | 120 | 0.4771 | 0.8006 |
83
- | 0.4297 | 0.97 | 130 | 0.4673 | 0.7987 |
84
- | 0.4658 | 1.04 | 140 | 0.4927 | 0.8063 |
85
- | 0.3992 | 1.12 | 150 | 0.4884 | 0.8121 |
86
- | 0.4752 | 1.19 | 160 | 0.4838 | 0.8102 |
87
- | 0.3934 | 1.27 | 170 | 0.4714 | 0.8092 |
88
- | 0.4662 | 1.34 | 180 | 0.5192 | 0.7929 |
89
- | 0.4404 | 1.42 | 190 | 0.4719 | 0.8111 |
90
- | 0.3746 | 1.49 | 200 | 0.5077 | 0.8015 |
91
- | 0.4465 | 1.57 | 210 | 0.4425 | 0.8073 |
92
- | 0.3829 | 1.64 | 220 | 0.4844 | 0.8130 |
93
- | 0.4021 | 1.72 | 230 | 0.4659 | 0.8169 |
94
- | 0.4225 | 1.79 | 240 | 0.4277 | 0.8130 |
95
- | 0.4297 | 1.87 | 250 | 0.4677 | 0.8150 |
96
- | 0.3476 | 1.94 | 260 | 0.4455 | 0.8207 |
97
- | 0.4159 | 2.01 | 270 | 0.5063 | 0.8188 |
98
- | 0.3371 | 2.09 | 280 | 0.4648 | 0.8265 |
99
- | 0.3383 | 2.16 | 290 | 0.5451 | 0.8178 |
100
- | 0.3175 | 2.24 | 300 | 0.4551 | 0.8303 |
101
- | 0.3553 | 2.31 | 310 | 0.4899 | 0.8303 |
102
- | 0.3138 | 2.39 | 320 | 0.4887 | 0.8265 |
103
- | 0.3196 | 2.46 | 330 | 0.4632 | 0.8265 |
104
- | 0.3132 | 2.54 | 340 | 0.5126 | 0.8207 |
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- | 0.3167 | 2.61 | 350 | 0.4661 | 0.8245 |
106
- | 0.3757 | 2.69 | 360 | 0.4596 | 0.8245 |
107
- | 0.3346 | 2.76 | 370 | 0.4650 | 0.8265 |
108
- | 0.3018 | 2.84 | 380 | 0.4672 | 0.8284 |
109
- | 0.3338 | 2.91 | 390 | 0.4822 | 0.8293 |
110
- | 0.3496 | 2.99 | 400 | 0.4677 | 0.8322 |
111
- | 0.248 | 3.06 | 410 | 0.4349 | 0.8332 |
112
- | 0.2804 | 3.13 | 420 | 0.5308 | 0.8322 |
113
- | 0.292 | 3.21 | 430 | 0.4757 | 0.8284 |
114
- | 0.249 | 3.28 | 440 | 0.5145 | 0.8284 |
115
- | 0.315 | 3.36 | 450 | 0.6137 | 0.8322 |
116
- | 0.2996 | 3.43 | 460 | 0.5499 | 0.8341 |
117
- | 0.2986 | 3.51 | 470 | 0.4774 | 0.8332 |
118
- | 0.3124 | 3.58 | 480 | 0.5733 | 0.8284 |
119
- | 0.2809 | 3.66 | 490 | 0.4938 | 0.8341 |
120
- | 0.213 | 3.73 | 500 | 0.5208 | 0.8332 |
121
- | 0.3106 | 3.81 | 510 | 0.4609 | 0.8322 |
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- | 0.2226 | 3.88 | 520 | 0.5320 | 0.8274 |
123
- | 0.3108 | 3.96 | 530 | 0.5457 | 0.8255 |
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- | 0.2456 | 4.03 | 540 | 0.4865 | 0.8322 |
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- | 0.223 | 4.1 | 550 | 0.5540 | 0.8313 |
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- | 0.1884 | 4.18 | 560 | 0.5363 | 0.8341 |
127
- | 0.1934 | 4.25 | 570 | 0.5706 | 0.8332 |
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- | 0.1793 | 4.33 | 580 | 0.5814 | 0.8322 |
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- | 0.2952 | 4.4 | 590 | 0.5305 | 0.8360 |
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- | 0.2915 | 4.48 | 600 | 0.5104 | 0.8332 |
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- | 0.259 | 4.55 | 610 | 0.5076 | 0.8428 |
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- | 0.2453 | 4.63 | 620 | 0.5188 | 0.8351 |
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- | 0.1903 | 4.7 | 630 | 0.5396 | 0.8399 |
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- | 0.2573 | 4.78 | 640 | 0.5584 | 0.8332 |
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- | 0.2787 | 4.85 | 650 | 0.5340 | 0.8360 |
136
- | 0.2256 | 4.93 | 660 | 0.5175 | 0.8351 |
137
- | 0.257 | 5.0 | 670 | 0.4482 | 0.8370 |
138
-
139
 
140
  ### Framework versions
141
 
142
- - Transformers 4.33.3
143
  - Pytorch 2.0.1+cu118
144
  - Datasets 2.14.5
145
- - Tokenizers 0.13.3
 
5
  - generated_from_trainer
6
  datasets:
7
  - glue
 
 
8
  model-index:
9
  - name: t5-base_cola_dense
10
+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
11
  ---
12
 
13
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
17
 
18
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
19
  It achieves the following results on the evaluation set:
20
+ - eval_loss: 0.6850
21
+ - eval_accuracy: 0.6088
22
+ - eval_runtime: 1.6155
23
+ - eval_samples_per_second: 645.626
24
+ - eval_steps_per_second: 10.523
25
+ - step: 0
26
 
27
  ## Model description
28
 
 
45
  - train_batch_size: 32
46
  - eval_batch_size: 64
47
  - seed: 42
 
48
  - gradient_accumulation_steps: 2
49
  - total_train_batch_size: 64
50
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
  - lr_scheduler_type: linear
52
  - lr_scheduler_warmup_steps: 200
53
+ - num_epochs: 0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
54
 
55
  ### Framework versions
56
 
57
+ - Transformers 4.34.0
58
  - Pytorch 2.0.1+cu118
59
  - Datasets 2.14.5
60
+ - Tokenizers 0.14.1
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