Instructions to use apssg96/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apssg96/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="apssg96/distilbert-base-uncased-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("apssg96/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("apssg96/distilbert-base-uncased-finetuned-emotion") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- .gitignore +1 -0
- config.json +41 -0
- pytorch_model.bin +3 -0
- runs/Mar01_18-16-33_a3a85f2b1521/1677694603.7395394/events.out.tfevents.1677694603.a3a85f2b1521.133.1 +3 -0
- runs/Mar01_18-16-33_a3a85f2b1521/events.out.tfevents.1677694603.a3a85f2b1521.133.0 +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +14 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
.gitignore
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checkpoint-*/
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.26.1",
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"vocab_size": 30522
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:07f15a4720e58581acb100b637bf02369535945af4cbb2c5cdc1caef93f0d185
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size 267867821
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runs/Mar01_18-16-33_a3a85f2b1521/1677694603.7395394/events.out.tfevents.1677694603.a3a85f2b1521.133.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:18e34a2e705fc1082111b388daab3bcce4df2774548f4d8a5fa599c76b924471
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size 5743
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runs/Mar01_18-16-33_a3a85f2b1521/events.out.tfevents.1677694603.a3a85f2b1521.133.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:82b66ef303c8b04b55496bfdb3709358efe82fbe2d07cf89e9e6e87fb195f166
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size 4727
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"name_or_path": "distilbert-base-uncased",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c793f38d3318d0f50bc0b3b45a7c4f93d4116151a50a439dee88bec89eb6796a
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size 3579
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vocab.txt
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