Hugging Face's logo

haryoaw
/
scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_155

Transformers
PyTorch
Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Community
haryoaw commited on
Commit
8f7569f
•
1 Parent(s): 779b14d

Initial Commit

Browse files
Files changed (4) hide show
  1. README.md +175 -0
  2. config.json +159 -0
  3. pytorch_model.bin +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,175 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: microsoft/mdeberta-v3-base
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - massive
8
+ metrics:
9
+ - accuracy
10
+ - f1
11
+ model-index:
12
+ - name: scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_155
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-SCR-MSV-D2_data-AmazonScience_massive_all_1_155
20
+
21
+ This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the massive dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: nan
24
+ - Accuracy: 0.0315
25
+ - F1: 0.0010
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: 55
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
+ | 0.0 | 0.27 | 5000 | nan | 0.0315 | 0.0010 |
57
+ | 0.0 | 0.53 | 10000 | nan | 0.0315 | 0.0010 |
58
+ | 0.0 | 0.8 | 15000 | nan | 0.0315 | 0.0010 |
59
+ | 0.0 | 1.07 | 20000 | nan | 0.0315 | 0.0010 |
60
+ | 0.0 | 1.34 | 25000 | nan | 0.0315 | 0.0010 |
61
+ | 0.0 | 1.6 | 30000 | nan | 0.0315 | 0.0010 |
62
+ | 0.0 | 1.87 | 35000 | nan | 0.0315 | 0.0010 |
63
+ | 0.0 | 2.14 | 40000 | nan | 0.0315 | 0.0010 |
64
+ | 0.0 | 2.41 | 45000 | nan | 0.0315 | 0.0010 |
65
+ | 0.0 | 2.67 | 50000 | nan | 0.0315 | 0.0010 |
66
+ | 0.0 | 2.94 | 55000 | nan | 0.0315 | 0.0010 |
67
+ | 0.0 | 3.21 | 60000 | nan | 0.0315 | 0.0010 |
68
+ | 0.0 | 3.47 | 65000 | nan | 0.0315 | 0.0010 |
69
+ | 0.0 | 3.74 | 70000 | nan | 0.0315 | 0.0010 |
70
+ | 0.0 | 4.01 | 75000 | nan | 0.0315 | 0.0010 |
71
+ | 0.0 | 4.28 | 80000 | nan | 0.0315 | 0.0010 |
72
+ | 0.0 | 4.54 | 85000 | nan | 0.0315 | 0.0010 |
73
+ | 0.0 | 4.81 | 90000 | nan | 0.0315 | 0.0010 |
74
+ | 0.0 | 5.08 | 95000 | nan | 0.0315 | 0.0010 |
75
+ | 0.0 | 5.34 | 100000 | nan | 0.0315 | 0.0010 |
76
+ | 0.0 | 5.61 | 105000 | nan | 0.0315 | 0.0010 |
77
+ | 0.0 | 5.88 | 110000 | nan | 0.0315 | 0.0010 |
78
+ | 0.0 | 6.15 | 115000 | nan | 0.0315 | 0.0010 |
79
+ | 0.0 | 6.41 | 120000 | nan | 0.0315 | 0.0010 |
80
+ | 0.0 | 6.68 | 125000 | nan | 0.0315 | 0.0010 |
81
+ | 0.0 | 6.95 | 130000 | nan | 0.0315 | 0.0010 |
82
+ | 0.0 | 7.22 | 135000 | nan | 0.0315 | 0.0010 |
83
+ | 0.0 | 7.48 | 140000 | nan | 0.0315 | 0.0010 |
84
+ | 0.0 | 7.75 | 145000 | nan | 0.0315 | 0.0010 |
85
+ | 0.0 | 8.02 | 150000 | nan | 0.0315 | 0.0010 |
86
+ | 0.0 | 8.28 | 155000 | nan | 0.0315 | 0.0010 |
87
+ | 0.0 | 8.55 | 160000 | nan | 0.0315 | 0.0010 |
88
+ | 0.0 | 8.82 | 165000 | nan | 0.0315 | 0.0010 |
89
+ | 0.0 | 9.09 | 170000 | nan | 0.0315 | 0.0010 |
90
+ | 0.0 | 9.35 | 175000 | nan | 0.0315 | 0.0010 |
91
+ | 0.0 | 9.62 | 180000 | nan | 0.0315 | 0.0010 |
92
+ | 0.0 | 9.89 | 185000 | nan | 0.0315 | 0.0010 |
93
+ | 0.0 | 10.15 | 190000 | nan | 0.0315 | 0.0010 |
94
+ | 0.0 | 10.42 | 195000 | nan | 0.0315 | 0.0010 |
95
+ | 0.0 | 10.69 | 200000 | nan | 0.0315 | 0.0010 |
96
+ | 0.0 | 10.96 | 205000 | nan | 0.0315 | 0.0010 |
97
+ | 0.0 | 11.22 | 210000 | nan | 0.0315 | 0.0010 |
98
+ | 0.0 | 11.49 | 215000 | nan | 0.0315 | 0.0010 |
99
+ | 0.0 | 11.76 | 220000 | nan | 0.0315 | 0.0010 |
100
+ | 0.0 | 12.03 | 225000 | nan | 0.0315 | 0.0010 |
101
+ | 0.0 | 12.29 | 230000 | nan | 0.0315 | 0.0010 |
102
+ | 0.0 | 12.56 | 235000 | nan | 0.0315 | 0.0010 |
103
+ | 0.0 | 12.83 | 240000 | nan | 0.0315 | 0.0010 |
104
+ | 0.0 | 13.09 | 245000 | nan | 0.0315 | 0.0010 |
105
+ | 0.0 | 13.36 | 250000 | nan | 0.0315 | 0.0010 |
106
+ | 0.0 | 13.63 | 255000 | nan | 0.0315 | 0.0010 |
107
+ | 0.0 | 13.9 | 260000 | nan | 0.0315 | 0.0010 |
108
+ | 0.0 | 14.16 | 265000 | nan | 0.0315 | 0.0010 |
109
+ | 0.0 | 14.43 | 270000 | nan | 0.0315 | 0.0010 |
110
+ | 0.0 | 14.7 | 275000 | nan | 0.0315 | 0.0010 |
111
+ | 0.0 | 14.96 | 280000 | nan | 0.0315 | 0.0010 |
112
+ | 0.0 | 15.23 | 285000 | nan | 0.0315 | 0.0010 |
113
+ | 0.0 | 15.5 | 290000 | nan | 0.0315 | 0.0010 |
114
+ | 0.0 | 15.77 | 295000 | nan | 0.0315 | 0.0010 |
115
+ | 0.0 | 16.03 | 300000 | nan | 0.0315 | 0.0010 |
116
+ | 0.0 | 16.3 | 305000 | nan | 0.0315 | 0.0010 |
117
+ | 0.0 | 16.57 | 310000 | nan | 0.0315 | 0.0010 |
118
+ | 0.0 | 16.84 | 315000 | nan | 0.0315 | 0.0010 |
119
+ | 0.0 | 17.1 | 320000 | nan | 0.0315 | 0.0010 |
120
+ | 0.0 | 17.37 | 325000 | nan | 0.0315 | 0.0010 |
121
+ | 0.0 | 17.64 | 330000 | nan | 0.0315 | 0.0010 |
122
+ | 0.0 | 17.9 | 335000 | nan | 0.0315 | 0.0010 |
123
+ | 0.0 | 18.17 | 340000 | nan | 0.0315 | 0.0010 |
124
+ | 0.0 | 18.44 | 345000 | nan | 0.0315 | 0.0010 |
125
+ | 0.0 | 18.71 | 350000 | nan | 0.0315 | 0.0010 |
126
+ | 0.0 | 18.97 | 355000 | nan | 0.0315 | 0.0010 |
127
+ | 0.0 | 19.24 | 360000 | nan | 0.0315 | 0.0010 |
128
+ | 0.0 | 19.51 | 365000 | nan | 0.0315 | 0.0010 |
129
+ | 0.0 | 19.77 | 370000 | nan | 0.0315 | 0.0010 |
130
+ | 0.0 | 20.04 | 375000 | nan | 0.0315 | 0.0010 |
131
+ | 0.0 | 20.31 | 380000 | nan | 0.0315 | 0.0010 |
132
+ | 0.0 | 20.58 | 385000 | nan | 0.0315 | 0.0010 |
133
+ | 0.0 | 20.84 | 390000 | nan | 0.0315 | 0.0010 |
134
+ | 0.0 | 21.11 | 395000 | nan | 0.0315 | 0.0010 |
135
+ | 0.0 | 21.38 | 400000 | nan | 0.0315 | 0.0010 |
136
+ | 0.0 | 21.65 | 405000 | nan | 0.0315 | 0.0010 |
137
+ | 0.0 | 21.91 | 410000 | nan | 0.0315 | 0.0010 |
138
+ | 0.0 | 22.18 | 415000 | nan | 0.0315 | 0.0010 |
139
+ | 0.0 | 22.45 | 420000 | nan | 0.0315 | 0.0010 |
140
+ | 0.0 | 22.71 | 425000 | nan | 0.0315 | 0.0010 |
141
+ | 0.0 | 22.98 | 430000 | nan | 0.0315 | 0.0010 |
142
+ | 0.0 | 23.25 | 435000 | nan | 0.0315 | 0.0010 |
143
+ | 0.0 | 23.52 | 440000 | nan | 0.0315 | 0.0010 |
144
+ | 0.0 | 23.78 | 445000 | nan | 0.0315 | 0.0010 |
145
+ | 0.0 | 24.05 | 450000 | nan | 0.0315 | 0.0010 |
146
+ | 0.0 | 24.32 | 455000 | nan | 0.0315 | 0.0010 |
147
+ | 0.0 | 24.58 | 460000 | nan | 0.0315 | 0.0010 |
148
+ | 0.0 | 24.85 | 465000 | nan | 0.0315 | 0.0010 |
149
+ | 0.0 | 25.12 | 470000 | nan | 0.0315 | 0.0010 |
150
+ | 0.0 | 25.39 | 475000 | nan | 0.0315 | 0.0010 |
151
+ | 0.0 | 25.65 | 480000 | nan | 0.0315 | 0.0010 |
152
+ | 0.0 | 25.92 | 485000 | nan | 0.0315 | 0.0010 |
153
+ | 0.0 | 26.19 | 490000 | nan | 0.0315 | 0.0010 |
154
+ | 0.0 | 26.46 | 495000 | nan | 0.0315 | 0.0010 |
155
+ | 0.0 | 26.72 | 500000 | nan | 0.0315 | 0.0010 |
156
+ | 0.0 | 26.99 | 505000 | nan | 0.0315 | 0.0010 |
157
+ | 0.0 | 27.26 | 510000 | nan | 0.0315 | 0.0010 |
158
+ | 0.0 | 27.52 | 515000 | nan | 0.0315 | 0.0010 |
159
+ | 0.0 | 27.79 | 520000 | nan | 0.0315 | 0.0010 |
160
+ | 0.0 | 28.06 | 525000 | nan | 0.0315 | 0.0010 |
161
+ | 0.0 | 28.33 | 530000 | nan | 0.0315 | 0.0010 |
162
+ | 0.0 | 28.59 | 535000 | nan | 0.0315 | 0.0010 |
163
+ | 0.0 | 28.86 | 540000 | nan | 0.0315 | 0.0010 |
164
+ | 0.0 | 29.13 | 545000 | nan | 0.0315 | 0.0010 |
165
+ | 0.0 | 29.39 | 550000 | nan | 0.0315 | 0.0010 |
166
+ | 0.0 | 29.66 | 555000 | nan | 0.0315 | 0.0010 |
167
+ | 0.0 | 29.93 | 560000 | nan | 0.0315 | 0.0010 |
168
+
169
+
170
+ ### Framework versions
171
+
172
+ - Transformers 4.33.3
173
+ - Pytorch 2.1.1+cu121
174
+ - Datasets 2.14.5
175
+ - Tokenizers 0.13.3
config.json ADDED
@@ -0,0 +1,159 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "microsoft/mdeberta-v3-base",
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
+ }
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:539f50454a47ee9189f572093f35d4ea5cb24b336ed7bccc53fd7f833b7099be
3
+ size 975227114
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9ca1368b5d04755dc8e4ae7db8bcd2456018ad885354416b525c037d1fc09696
3
+ size 4600