Hugging Face's logo

haryoaw
/
scenario-KD-PO-MSV-CL-D2_data-cl-massive_all_1_166

PyTorch
deberta-v2
Generated from Trainer
Model card Files Community
haryoaw commited on
Commit
63982c5
•
1 Parent(s): c2c5b56

Initial Commit

Browse files
Files changed (5) hide show
  1. README.md +116 -0
  2. config.json +159 -0
  3. eval_results_ml.json +1 -0
  4. pytorch_model.bin +3 -0
  5. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,116 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: haryoaw/scenario-MDBT-TCR_data-cl-massive_all_1_1
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - massive
8
+ metrics:
9
+ - accuracy
10
+ - f1
11
+ model-index:
12
+ - name: scenario-KD-PO-MSV-CL-D2_data-cl-massive_all_1_166
13
+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
+ should probably proofread and complete it, then remove this comment. -->
18
+
19
+ # scenario-KD-PO-MSV-CL-D2_data-cl-massive_all_1_166
20
+
21
+ This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cl-massive_all_1_1](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cl-massive_all_1_1) on the massive dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: 6.0186
24
+ - Accuracy: 0.6461
25
+ - F1: 0.6134
26
+
27
+ ## Model description
28
+
29
+ More information needed
30
+
31
+ ## Intended uses & limitations
32
+
33
+ More information needed
34
+
35
+ ## Training and evaluation data
36
+
37
+ More information needed
38
+
39
+ ## Training procedure
40
+
41
+ ### Training hyperparameters
42
+
43
+ The following hyperparameters were used during training:
44
+ - learning_rate: 5e-05
45
+ - train_batch_size: 32
46
+ - eval_batch_size: 32
47
+ - seed: 66
48
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
+ - lr_scheduler_type: linear
50
+ - num_epochs: 30
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
55
+ |:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
56
+ | 2.2524 | 0.56 | 5000 | 5.6187 | 0.6299 | 0.5728 |
57
+ | 1.3325 | 1.11 | 10000 | 5.4671 | 0.6450 | 0.5924 |
58
+ | 1.2156 | 1.67 | 15000 | 6.0747 | 0.6250 | 0.5912 |
59
+ | 0.8855 | 2.22 | 20000 | 5.8471 | 0.6355 | 0.5857 |
60
+ | 0.8518 | 2.78 | 25000 | 6.2545 | 0.6303 | 0.5845 |
61
+ | 0.6853 | 3.33 | 30000 | 6.0057 | 0.6408 | 0.6017 |
62
+ | 0.6658 | 3.89 | 35000 | 6.0161 | 0.6423 | 0.6002 |
63
+ | 0.5544 | 4.45 | 40000 | 6.0854 | 0.6392 | 0.6006 |
64
+ | 0.5357 | 5.0 | 45000 | 6.2732 | 0.6283 | 0.5888 |
65
+ | 0.4924 | 5.56 | 50000 | 6.4624 | 0.6277 | 0.5952 |
66
+ | 0.4369 | 6.11 | 55000 | 6.2119 | 0.6354 | 0.5944 |
67
+ | 0.4276 | 6.67 | 60000 | 6.2395 | 0.6425 | 0.6006 |
68
+ | 0.3974 | 7.23 | 65000 | 6.6542 | 0.6264 | 0.5893 |
69
+ | 0.404 | 7.78 | 70000 | 6.4174 | 0.6295 | 0.5975 |
70
+ | 0.3763 | 8.34 | 75000 | 6.1405 | 0.6426 | 0.6025 |
71
+ | 0.3719 | 8.89 | 80000 | 6.4745 | 0.6346 | 0.6024 |
72
+ | 0.3428 | 9.45 | 85000 | 5.9964 | 0.6389 | 0.6030 |
73
+ | 0.3288 | 10.0 | 90000 | 6.3213 | 0.6335 | 0.5988 |
74
+ | 0.3192 | 10.56 | 95000 | 6.4269 | 0.6321 | 0.5937 |
75
+ | 0.2934 | 11.12 | 100000 | 6.3224 | 0.6392 | 0.6039 |
76
+ | 0.3054 | 11.67 | 105000 | 6.4531 | 0.6326 | 0.5989 |
77
+ | 0.2841 | 12.23 | 110000 | 6.2824 | 0.6360 | 0.6075 |
78
+ | 0.2915 | 12.78 | 115000 | 6.1928 | 0.6391 | 0.6039 |
79
+ | 0.274 | 13.34 | 120000 | 6.1931 | 0.6401 | 0.6030 |
80
+ | 0.2776 | 13.9 | 125000 | 6.2524 | 0.6384 | 0.6045 |
81
+ | 0.2724 | 14.45 | 130000 | 5.9260 | 0.6456 | 0.6090 |
82
+ | 0.2602 | 15.01 | 135000 | 6.3508 | 0.6347 | 0.6052 |
83
+ | 0.2627 | 15.56 | 140000 | 6.1761 | 0.6421 | 0.6074 |
84
+ | 0.2496 | 16.12 | 145000 | 6.1398 | 0.6391 | 0.6111 |
85
+ | 0.253 | 16.67 | 150000 | 6.2431 | 0.6328 | 0.6014 |
86
+ | 0.2451 | 17.23 | 155000 | 6.1746 | 0.6378 | 0.6048 |
87
+ | 0.2369 | 17.79 | 160000 | 6.0915 | 0.6435 | 0.6103 |
88
+ | 0.2332 | 18.34 | 165000 | 6.2138 | 0.6376 | 0.6071 |
89
+ | 0.2325 | 18.9 | 170000 | 6.1176 | 0.6433 | 0.6073 |
90
+ | 0.2239 | 19.45 | 175000 | 5.9650 | 0.6419 | 0.6068 |
91
+ | 0.2229 | 20.01 | 180000 | 6.2025 | 0.6395 | 0.6072 |
92
+ | 0.2241 | 20.56 | 185000 | 6.0510 | 0.6418 | 0.6088 |
93
+ | 0.212 | 21.12 | 190000 | 5.9952 | 0.6438 | 0.6100 |
94
+ | 0.218 | 21.68 | 195000 | 6.2810 | 0.6376 | 0.6073 |
95
+ | 0.212 | 22.23 | 200000 | 5.9274 | 0.6454 | 0.6076 |
96
+ | 0.2091 | 22.79 | 205000 | 6.1958 | 0.6367 | 0.6071 |
97
+ | 0.2091 | 23.34 | 210000 | 5.9633 | 0.6463 | 0.6153 |
98
+ | 0.2065 | 23.9 | 215000 | 6.0132 | 0.6458 | 0.6116 |
99
+ | 0.2048 | 24.46 | 220000 | 5.9809 | 0.6451 | 0.6132 |
100
+ | 0.1996 | 25.01 | 225000 | 6.1021 | 0.6389 | 0.6063 |
101
+ | 0.1966 | 25.57 | 230000 | 5.9612 | 0.6448 | 0.6140 |
102
+ | 0.1964 | 26.12 | 235000 | 6.0715 | 0.6434 | 0.6134 |
103
+ | 0.1971 | 26.68 | 240000 | 6.0237 | 0.6442 | 0.6127 |
104
+ | 0.1893 | 27.23 | 245000 | 6.0213 | 0.6418 | 0.6086 |
105
+ | 0.1891 | 27.79 | 250000 | 6.0386 | 0.6445 | 0.6127 |
106
+ | 0.1942 | 28.35 | 255000 | 6.0043 | 0.6428 | 0.6099 |
107
+ | 0.1966 | 28.9 | 260000 | 5.9983 | 0.6440 | 0.6130 |
108
+ | 0.1883 | 29.46 | 265000 | 6.0186 | 0.6461 | 0.6134 |
109
+
110
+
111
+ ### Framework versions
112
+
113
+ - Transformers 4.33.3
114
+ - Pytorch 2.1.1+cu121
115
+ - Datasets 2.14.5
116
+ - Tokenizers 0.13.3
config.json ADDED
@@ -0,0 +1,159 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "haryoaw/scenario-MDBT-TCR_data-cl-massive_all_1_1",
3
+ "architectures": [
4
+ "DebertaForSequenceClassificationKD"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "hidden_act": "gelu",
8
+ "hidden_dropout_prob": 0.1,
9
+ "hidden_size": 768,
10
+ "id2label": {
11
+ "0": "LABEL_0",
12
+ "1": "LABEL_1",
13
+ "2": "LABEL_2",
14
+ "3": "LABEL_3",
15
+ "4": "LABEL_4",
16
+ "5": "LABEL_5",
17
+ "6": "LABEL_6",
18
+ "7": "LABEL_7",
19
+ "8": "LABEL_8",
20
+ "9": "LABEL_9",
21
+ "10": "LABEL_10",
22
+ "11": "LABEL_11",
23
+ "12": "LABEL_12",
24
+ "13": "LABEL_13",
25
+ "14": "LABEL_14",
26
+ "15": "LABEL_15",
27
+ "16": "LABEL_16",
28
+ "17": "LABEL_17",
29
+ "18": "LABEL_18",
30
+ "19": "LABEL_19",
31
+ "20": "LABEL_20",
32
+ "21": "LABEL_21",
33
+ "22": "LABEL_22",
34
+ "23": "LABEL_23",
35
+ "24": "LABEL_24",
36
+ "25": "LABEL_25",
37
+ "26": "LABEL_26",
38
+ "27": "LABEL_27",
39
+ "28": "LABEL_28",
40
+ "29": "LABEL_29",
41
+ "30": "LABEL_30",
42
+ "31": "LABEL_31",
43
+ "32": "LABEL_32",
44
+ "33": "LABEL_33",
45
+ "34": "LABEL_34",
46
+ "35": "LABEL_35",
47
+ "36": "LABEL_36",
48
+ "37": "LABEL_37",
49
+ "38": "LABEL_38",
50
+ "39": "LABEL_39",
51
+ "40": "LABEL_40",
52
+ "41": "LABEL_41",
53
+ "42": "LABEL_42",
54
+ "43": "LABEL_43",
55
+ "44": "LABEL_44",
56
+ "45": "LABEL_45",
57
+ "46": "LABEL_46",
58
+ "47": "LABEL_47",
59
+ "48": "LABEL_48",
60
+ "49": "LABEL_49",
61
+ "50": "LABEL_50",
62
+ "51": "LABEL_51",
63
+ "52": "LABEL_52",
64
+ "53": "LABEL_53",
65
+ "54": "LABEL_54",
66
+ "55": "LABEL_55",
67
+ "56": "LABEL_56",
68
+ "57": "LABEL_57",
69
+ "58": "LABEL_58",
70
+ "59": "LABEL_59"
71
+ },
72
+ "initializer_range": 0.02,
73
+ "intermediate_size": 3072,
74
+ "label2id": {
75
+ "LABEL_0": 0,
76
+ "LABEL_1": 1,
77
+ "LABEL_10": 10,
78
+ "LABEL_11": 11,
79
+ "LABEL_12": 12,
80
+ "LABEL_13": 13,
81
+ "LABEL_14": 14,
82
+ "LABEL_15": 15,
83
+ "LABEL_16": 16,
84
+ "LABEL_17": 17,
85
+ "LABEL_18": 18,
86
+ "LABEL_19": 19,
87
+ "LABEL_2": 2,
88
+ "LABEL_20": 20,
89
+ "LABEL_21": 21,
90
+ "LABEL_22": 22,
91
+ "LABEL_23": 23,
92
+ "LABEL_24": 24,
93
+ "LABEL_25": 25,
94
+ "LABEL_26": 26,
95
+ "LABEL_27": 27,
96
+ "LABEL_28": 28,
97
+ "LABEL_29": 29,
98
+ "LABEL_3": 3,
99
+ "LABEL_30": 30,
100
+ "LABEL_31": 31,
101
+ "LABEL_32": 32,
102
+ "LABEL_33": 33,
103
+ "LABEL_34": 34,
104
+ "LABEL_35": 35,
105
+ "LABEL_36": 36,
106
+ "LABEL_37": 37,
107
+ "LABEL_38": 38,
108
+ "LABEL_39": 39,
109
+ "LABEL_4": 4,
110
+ "LABEL_40": 40,
111
+ "LABEL_41": 41,
112
+ "LABEL_42": 42,
113
+ "LABEL_43": 43,
114
+ "LABEL_44": 44,
115
+ "LABEL_45": 45,
116
+ "LABEL_46": 46,
117
+ "LABEL_47": 47,
118
+ "LABEL_48": 48,
119
+ "LABEL_49": 49,
120
+ "LABEL_5": 5,
121
+ "LABEL_50": 50,
122
+ "LABEL_51": 51,
123
+ "LABEL_52": 52,
124
+ "LABEL_53": 53,
125
+ "LABEL_54": 54,
126
+ "LABEL_55": 55,
127
+ "LABEL_56": 56,
128
+ "LABEL_57": 57,
129
+ "LABEL_58": 58,
130
+ "LABEL_59": 59,
131
+ "LABEL_6": 6,
132
+ "LABEL_7": 7,
133
+ "LABEL_8": 8,
134
+ "LABEL_9": 9
135
+ },
136
+ "layer_norm_eps": 1e-07,
137
+ "max_position_embeddings": 512,
138
+ "max_relative_positions": -1,
139
+ "model_type": "deberta-v2",
140
+ "norm_rel_ebd": "layer_norm",
141
+ "num_attention_heads": 12,
142
+ "num_hidden_layers": 6,
143
+ "pad_token_id": 0,
144
+ "pooler_dropout": 0,
145
+ "pooler_hidden_act": "gelu",
146
+ "pooler_hidden_size": 768,
147
+ "pos_att_type": [
148
+ "p2c",
149
+ "c2p"
150
+ ],
151
+ "position_biased_input": false,
152
+ "position_buckets": 256,
153
+ "relative_attention": true,
154
+ "share_att_key": true,
155
+ "torch_dtype": "float32",
156
+ "transformers_version": "4.33.3",
157
+ "type_vocab_size": 0,
158
+ "vocab_size": 251000
159
+ }
eval_results_ml.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"ar-SA": {"f1": 0.7720010663747154, "accuracy": 0.8264963012777404}, "he-IL": {"f1": 0.5745824369450304, "accuracy": 0.6610625420309347}, "pt-PT": {"f1": 0.8324502237245487, "accuracy": 0.875252185608608}, "fi-FI": {"f1": 0.8154091746380266, "accuracy": 0.8607935440484197}, "kn-IN": {"f1": 0.5780343670831116, "accuracy": 0.6506388702084734}, "ca-ES": {"f1": 0.7358548975506386, "accuracy": 0.7780766644250168}, "da-DK": {"f1": 0.737668214092637, "accuracy": 0.8029589778076665}, "ro-RO": {"f1": 0.6477681422714716, "accuracy": 0.7246133154001345}, "pl-PL": {"f1": 0.6621571909069583, "accuracy": 0.7609280430396772}, "en-US": {"f1": 0.8506893531708493, "accuracy": 0.8930733019502354}, "de-DE": {"f1": 0.8190904756196555, "accuracy": 0.8705447209145931}, "ms-MY": {"f1": 0.6936443014436624, "accuracy": 0.7589105581708138}, "jv-ID": {"f1": 0.8272182809538818, "accuracy": 0.8597848016139878}, "ta-IN": {"f1": 0.5849528463090181, "accuracy": 0.6792199058507061}, "hu-HU": {"f1": 0.8235842095940068, "accuracy": 0.8742434431741762}, "id-ID": {"f1": 0.8277902807365753, "accuracy": 0.8772696704774714}, "th-TH": {"f1": 0.7601694366157717, "accuracy": 0.7881640887693342}, "ko-KR": {"f1": 0.8258340149702332, "accuracy": 0.8739071956960323}, "tl-PH": {"f1": 0.41221233107481825, "accuracy": 0.46234028244788167}, "bn-BD": {"f1": 0.8222195031892248, "accuracy": 0.8547410894418291}, "az-AZ": {"f1": 0.6379146919077101, "accuracy": 0.7064559515803631}, "zh-TW": {"f1": 0.8219476802602138, "accuracy": 0.85137861466039}, "cy-GB": {"f1": 0.15360224910725706, "accuracy": 0.23806321452589105}, "sq-AL": {"f1": 0.5203060184356132, "accuracy": 0.562542030934768}, "ru-RU": {"f1": 0.8360932583374457, "accuracy": 0.879287155346335}, "af-ZA": {"f1": 0.580146501173271, "accuracy": 0.6492938802958977}, "fr-FR": {"f1": 0.8321333798384362, "accuracy": 0.878950907868191}, "ka-GE": {"f1": 0.783785888663372, "accuracy": 0.8221250840618696}, "is-IS": {"f1": 0.8202059436401666, "accuracy": 0.8651647612642905}, "sw-KE": {"f1": 0.38820124799934286, "accuracy": 0.4589778076664425}, "hi-IN": {"f1": 0.8122286015860652, "accuracy": 0.8655010087424344}, "km-KH": {"f1": 0.557996205283102, "accuracy": 0.6304640215198386}, "lv-LV": {"f1": 0.8434795040666275, "accuracy": 0.8708809683927371}, "sl-SL": {"f1": 0.546698528124086, "accuracy": 0.5998655010087425}, "am-ET": {"f1": 0.21524690087379741, "accuracy": 0.28681909885675855}, "sv-SE": {"f1": 0.7274340266407211, "accuracy": 0.8016139878950908}, "mn-MN": {"f1": 0.4589313676752772, "accuracy": 0.5336247478143914}, "my-MM": {"f1": 0.8163612617095788, "accuracy": 0.8604572965702757}, "ja-JP": {"f1": 0.8502108894924849, "accuracy": 0.8806321452589105}, "ur-PK": {"f1": 0.4160032989982115, "accuracy": 0.4761264290517821}, "it-IT": {"f1": 0.7211923887655927, "accuracy": 0.796906523201076}, "nb-NO": {"f1": 0.753965178683486, "accuracy": 0.8080026899798252}, "te-IN": {"f1": 0.5170677460146224, "accuracy": 0.6116341627437795}, "zh-CN": {"f1": 0.8207813034678526, "accuracy": 0.8644922663080027}, "fa-IR": {"f1": 0.6535974427037031, "accuracy": 0.734364492266308}, "tr-TR": {"f1": 0.8210590707934682, "accuracy": 0.8705447209145931}, "vi-VN": {"f1": 0.8224631444887968, "accuracy": 0.8695359784801614}, "nl-NL": {"f1": 0.7347664077644604, "accuracy": 0.8093476798924009}, "es-ES": {"f1": 0.8385495149569755, "accuracy": 0.8765971755211835}, "hy-AM": {"f1": 0.8048019679896729, "accuracy": 0.8597848016139878}, "el-GR": {"f1": 0.8213653641875498, "accuracy": 0.867182246133154}, "ml-IN": {"f1": 0.5759394269035711, "accuracy": 0.6872898453261601}, "all": {"f1": 0.7090860083539934, "accuracy": 0.7522114737985619}}
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e221f49cbacf50a59444f5848e249da7b9959cd435f291fe75a68f1b0f615871
3
+ size 946915690
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:54fbaee59da33615188679b7bc74c8f0a604f47193908380a5a628aab16bd662
3
+ size 4600