Instructions to use ShihHsuanChen/deberta-v3-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShihHsuanChen/deberta-v3-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ShihHsuanChen/deberta-v3-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ShihHsuanChen/deberta-v3-emotion") model = AutoModelForSequenceClassification.from_pretrained("ShihHsuanChen/deberta-v3-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
f7a7507
0
Parent(s):
INIT
Browse files- .gitattributes +1 -0
- README.md +0 -0
- config.json +51 -0
- model.safetensors +3 -0
- train_config.json +1 -0
- train_log.csv +21 -0
.gitattributes
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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README.md
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File without changes
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config.json
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{
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"architectures": [
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"DebertaV2ForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "sadness",
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"1": "joy",
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"2": "love",
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"3": "anger",
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"4": "fear",
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"5": "surprise"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"anger": 3,
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"fear": 4,
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"joy": 1,
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"love": 2,
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"sadness": 0,
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"surprise": 5
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},
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"layer_norm_eps": 1e-07,
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"legacy": true,
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"max_position_embeddings": 512,
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"max_relative_positions": -1,
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"model_type": "deberta-v2",
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"norm_rel_ebd": "layer_norm",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_dropout": 0,
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"pooler_hidden_act": "gelu",
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"pooler_hidden_size": 768,
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"pos_att_type": [
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"p2c",
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"c2p"
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],
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"position_biased_input": false,
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"position_buckets": 256,
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"relative_attention": true,
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"share_att_key": true,
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"torch_dtype": "float32",
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"transformers_version": "4.51.3",
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"type_vocab_size": 0,
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"vocab_size": 128100
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:be53921899723ea498ad2ececca0fddbc4e3a679147b7935903bf83ae645c7b9
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size 737731584
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train_config.json
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{"seed": 567, "ddp": true, "learning_rate": 5e-05, "train_batch_size": 80, "valid_batch_size": 80, "lr_scheduler_type": "linear", "num_epochs": 20, "num_warmup_steps": 125, "max_train_steps": null, "max_valid_steps": null, "max_length": 72}
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train_log.csv
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epoch,lr,train_loss,valid_loss,valid_accuracy
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1,4e-05,0.6908868551254272,0.6089823941389719,0.8083333422740301
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2,4.8001066098081025e-05,0.3298718333244324,0.19640956446528435,0.9239583512147268
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3,4.5335820895522394e-05,0.19889609515666962,0.13936338853091002,0.940625011920929
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4,4.2670575692963755e-05,0.12645851075649261,0.11494975987200935,0.9489583472410837
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5,4.000533049040512e-05,0.09315995872020721,0.11977107791850965,0.9468750158945719
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6,3.7340085287846486e-05,0.08274087309837341,0.1362296549292902,0.9375000099341074
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7,3.467484008528785e-05,0.07604973763227463,0.1645363668600718,0.939583346247673
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8,3.200959488272921e-05,0.057310208678245544,0.16730575651551285,0.9343750129143397
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9,2.934434968017058e-05,0.0632554441690445,0.1683110591645042,0.9437500139077505
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10,2.6679104477611942e-05,0.08436565846204758,0.19473591508964697,0.9447916746139526
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11,2.4013859275053304e-05,0.01617152988910675,0.18308352880800763,0.9416666626930237
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12,2.1348614072494673e-05,0.03712035343050957,0.21083885338157415,0.9479166716337204
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13,1.8683368869936034e-05,0.021857302635908127,0.2227405613909165,0.940625011920929
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14,1.60181236673774e-05,0.004591828212141991,0.25835480727255344,0.9406250069538752
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15,1.3352878464818763e-05,0.009411506354808807,0.2548551845053832,0.9354166785875956
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16,1.0687633262260128e-05,0.0017591080395504832,0.24660054633083442,0.9385416706403097
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17,8.022388059701493e-06,0.001765915541909635,0.2517154838424176,0.9416666726271311
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18,5.357142857142857e-06,0.001407127594575286,0.2756552553425233,0.9375000049670538
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19,2.6918976545842217e-06,0.0009788793977349997,0.2826926866546273,0.9364583442608515
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20,2.6652452025586355e-08,0.0011572353541851044,0.28512330415348214,0.9364583442608515
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