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roberta-base-mnli-negnli

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Thinh Truong commited on
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update model files

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  1. README.md +56 -0
  2. all_results.json +14 -0
  3. config.json +38 -0
  4. eval_results.json +9 -0
  5. merges.txt +0 -0
  6. pytorch_model.bin +3 -0
  7. roberta2-base-mnli-negnli/README.md +56 -0
  8. roberta2-base-mnli-negnli/all_results.json +14 -0
  9. roberta2-base-mnli-negnli/checkpoint-500/config.json +38 -0
  10. roberta2-base-mnli-negnli/checkpoint-500/merges.txt +0 -0
  11. roberta2-base-mnli-negnli/checkpoint-500/optimizer.pt +3 -0
  12. roberta2-base-mnli-negnli/checkpoint-500/pytorch_model.bin +3 -0
  13. roberta2-base-mnli-negnli/checkpoint-500/rng_state.pth +3 -0
  14. roberta2-base-mnli-negnli/checkpoint-500/scheduler.pt +3 -0
  15. roberta2-base-mnli-negnli/checkpoint-500/special_tokens_map.json +15 -0
  16. roberta2-base-mnli-negnli/checkpoint-500/tokenizer.json +0 -0
  17. roberta2-base-mnli-negnli/checkpoint-500/tokenizer_config.json +16 -0
  18. roberta2-base-mnli-negnli/checkpoint-500/trainer_state.json +22 -0
  19. roberta2-base-mnli-negnli/checkpoint-500/training_args.bin +3 -0
  20. roberta2-base-mnli-negnli/checkpoint-500/vocab.json +0 -0
  21. roberta2-base-mnli-negnli/config.json +38 -0
  22. roberta2-base-mnli-negnli/eval_results.json +9 -0
  23. roberta2-base-mnli-negnli/merges.txt +0 -0
  24. roberta2-base-mnli-negnli/pytorch_model.bin +3 -0
  25. roberta2-base-mnli-negnli/runs/Jul07_23-50-30_doe/1657201850.622683/events.out.tfevents.1657201850.doe.63764.1 +3 -0
  26. roberta2-base-mnli-negnli/runs/Jul07_23-50-30_doe/events.out.tfevents.1657201850.doe.63764.0 +3 -0
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  34. roberta2-base-mnli-negnli/runs/Jul08_01-08-17_doe/1657206517.7561595/events.out.tfevents.1657206517.doe.16385.1 +3 -0
  35. roberta2-base-mnli-negnli/runs/Jul08_01-08-17_doe/events.out.tfevents.1657206517.doe.16385.0 +3 -0
  36. roberta2-base-mnli-negnli/runs/Jul08_01-08-17_doe/events.out.tfevents.1657206612.doe.16385.2 +3 -0
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  38. roberta2-base-mnli-negnli/runs/Jul08_01-12-22_doe/events.out.tfevents.1657206761.doe.20937.0 +3 -0
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  44. roberta2-base-mnli-negnli/runs/Jul08_01-22-31_doe/events.out.tfevents.1657207371.doe.33741.0 +3 -0
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  46. roberta2-base-mnli-negnli/special_tokens_map.json +15 -0
  47. roberta2-base-mnli-negnli/tokenizer.json +0 -0
  48. roberta2-base-mnli-negnli/tokenizer_config.json +16 -0
  49. roberta2-base-mnli-negnli/train_results.json +8 -0
  50. roberta2-base-mnli-negnli/trainer_state.json +31 -0
README.md ADDED
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1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: roberta2-base-mnli-negnli
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # roberta2-base-mnli-negnli
16
+
17
+ This model is a fine-tuned version of [sileod/roberta-base-mnli](https://huggingface.co/sileod/roberta-base-mnli) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.8397
20
+ - Accuracy: 0.8400
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 2e-05
40
+ - train_batch_size: 8
41
+ - eval_batch_size: 8
42
+ - seed: 42
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 5.0
46
+
47
+ ### Training results
48
+
49
+
50
+
51
+ ### Framework versions
52
+
53
+ - Transformers 4.21.0.dev0
54
+ - Pytorch 1.8.0
55
+ - Datasets 1.18.3
56
+ - Tokenizers 0.12.1
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+ {
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+ "epoch": 5.0,
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+ "eval_accuracy": 0.8399999737739563,
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+ "train_loss": 0.444431884765625,
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+ "train_samples": 1200,
12
+ "train_samples_per_second": 37.877,
13
+ "train_steps_per_second": 4.735
14
+ }
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1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: roberta2-base-mnli-negnli
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # roberta2-base-mnli-negnli
16
+
17
+ This model is a fine-tuned version of [sileod/roberta-base-mnli](https://huggingface.co/sileod/roberta-base-mnli) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.8397
20
+ - Accuracy: 0.8400
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 2e-05
40
+ - train_batch_size: 8
41
+ - eval_batch_size: 8
42
+ - seed: 42
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 5.0
46
+
47
+ ### Training results
48
+
49
+
50
+
51
+ ### Framework versions
52
+
53
+ - Transformers 4.21.0.dev0
54
+ - Pytorch 1.8.0
55
+ - Datasets 1.18.3
56
+ - Tokenizers 0.12.1
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+ }
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