Hugging Face's logo

haryoaw
/
scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_c

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
haryoaw commited on
Commit
3609c3f
•
1 Parent(s): fc9b2fd

Initial Commit

Browse files
Files changed (3) hide show
  1. README.md +35 -14
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -23,10 +23,10 @@ model-index:
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
- value: 0.3333333333333333
27
  - name: F1
28
  type: f1
29
- value: 0.16666666666666666
30
  ---
31
 
32
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
36
 
37
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the tweet_sentiment_multilingual dataset.
38
  It achieves the following results on the evaluation set:
39
- - Loss: 1.0996
40
- - Accuracy: 0.3333
41
- - F1: 0.1667
42
 
43
  ## Model description
44
 
@@ -57,7 +57,7 @@ More information needed
57
  ### Training hyperparameters
58
 
59
  The following hyperparameters were used during training:
60
- - learning_rate: 5e-05
61
  - train_batch_size: 32
62
  - eval_batch_size: 32
63
  - seed: 134
@@ -67,14 +67,35 @@ The following hyperparameters were used during training:
67
 
68
  ### Training results
69
 
70
- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
71
- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
72
- | 1.0904 | 1.09 | 500 | 1.0988 | 0.3341 | 0.1691 |
73
- | 1.104 | 2.17 | 1000 | 1.0991 | 0.3333 | 0.1667 |
74
- | 1.103 | 3.26 | 1500 | 1.0996 | 0.3333 | 0.1667 |
75
- | 1.1046 | 4.35 | 2000 | 1.0991 | 0.3333 | 0.1667 |
76
- | 1.1019 | 5.43 | 2500 | 1.0989 | 0.3333 | 0.1667 |
77
- | 1.1025 | 6.52 | 3000 | 1.0996 | 0.3333 | 0.1667 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78
 
79
 
80
  ### Framework versions
 
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
+ value: 0.6431327160493827
27
  - name: F1
28
  type: f1
29
+ value: 0.6424433208447596
30
  ---
31
 
32
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
36
 
37
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the tweet_sentiment_multilingual dataset.
38
  It achieves the following results on the evaluation set:
39
+ - Loss: 2.5108
40
+ - Accuracy: 0.6431
41
+ - F1: 0.6424
42
 
43
  ## Model description
44
 
 
57
  ### Training hyperparameters
58
 
59
  The following hyperparameters were used during training:
60
+ - learning_rate: 1e-05
61
  - train_batch_size: 32
62
  - eval_batch_size: 32
63
  - seed: 134
 
67
 
68
  ### Training results
69
 
70
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
71
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
72
+ | 0.9471 | 1.09 | 500 | 0.8205 | 0.6412 | 0.6387 |
73
+ | 0.7916 | 2.17 | 1000 | 0.8077 | 0.6474 | 0.6462 |
74
+ | 0.6978 | 3.26 | 1500 | 0.8621 | 0.6528 | 0.6534 |
75
+ | 0.6176 | 4.35 | 2000 | 0.9091 | 0.6412 | 0.6363 |
76
+ | 0.5422 | 5.43 | 2500 | 0.9120 | 0.6454 | 0.6440 |
77
+ | 0.4822 | 6.52 | 3000 | 0.9097 | 0.6512 | 0.6469 |
78
+ | 0.4117 | 7.61 | 3500 | 1.0223 | 0.6420 | 0.6406 |
79
+ | 0.3669 | 8.7 | 4000 | 1.1259 | 0.6404 | 0.6427 |
80
+ | 0.3229 | 9.78 | 4500 | 1.2050 | 0.6516 | 0.6489 |
81
+ | 0.2797 | 10.87 | 5000 | 1.2616 | 0.6408 | 0.6415 |
82
+ | 0.2657 | 11.96 | 5500 | 1.3181 | 0.6435 | 0.6412 |
83
+ | 0.226 | 13.04 | 6000 | 1.4459 | 0.6400 | 0.6424 |
84
+ | 0.2123 | 14.13 | 6500 | 1.5978 | 0.6389 | 0.6379 |
85
+ | 0.1853 | 15.22 | 7000 | 1.6409 | 0.6412 | 0.6438 |
86
+ | 0.1759 | 16.3 | 7500 | 1.6756 | 0.6485 | 0.6495 |
87
+ | 0.1579 | 17.39 | 8000 | 1.6652 | 0.6412 | 0.6418 |
88
+ | 0.1409 | 18.48 | 8500 | 1.9476 | 0.6389 | 0.6384 |
89
+ | 0.1282 | 19.57 | 9000 | 2.0246 | 0.6285 | 0.6280 |
90
+ | 0.1254 | 20.65 | 9500 | 1.9803 | 0.6412 | 0.6437 |
91
+ | 0.1077 | 21.74 | 10000 | 2.0991 | 0.6447 | 0.6429 |
92
+ | 0.097 | 22.83 | 10500 | 2.1971 | 0.6424 | 0.6413 |
93
+ | 0.0965 | 23.91 | 11000 | 2.2161 | 0.6420 | 0.6387 |
94
+ | 0.0859 | 25.0 | 11500 | 2.3387 | 0.6346 | 0.6329 |
95
+ | 0.0744 | 26.09 | 12000 | 2.3921 | 0.6466 | 0.6458 |
96
+ | 0.0693 | 27.17 | 12500 | 2.4696 | 0.6424 | 0.6428 |
97
+ | 0.072 | 28.26 | 13000 | 2.5027 | 0.6435 | 0.6431 |
98
+ | 0.0701 | 29.35 | 13500 | 2.5108 | 0.6431 | 0.6424 |
99
 
100
 
101
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:abc32e4d5608e3db44695ca4be4137757d0ee3c8929af49e3e2941e3edec363b
3
  size 1112253230
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e7f72966516717e4c8d9294af8b341a9664f7f0fe590edbc150e14fb1edfd30c
3
  size 1112253230
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9644fe57a140e43f1dfa562480571e79f216a46936a99a67dddbd9f3c63665b0
3
  size 4600
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ac3d44e8c03e821ee202b4e4f3ef41911154676e5b503f6381c962f69e37a7ae
3
  size 4600