davidliu0716
commited on
Commit
•
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Parent(s):
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Training completed!
Browse files- README.md +64 -0
- added_tokens.json +7 -0
- config.json +229 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +56 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: distilbert-base-uncased-finetuned-language
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# distilbert-base-uncased-finetuned-language
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0408
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- Accuracy: 0.9932
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- F1: 0.9932
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- distributed_type: tpu
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.2088 | 1.0 | 2188 | 0.0386 | 0.9927 | 0.9927 |
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| 0.0105 | 2.0 | 4376 | 0.0408 | 0.9932 | 0.9932 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.0
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added_tokens.json
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{
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"[CLS]": 101,
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"[MASK]": 103,
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"[PAD]": 0,
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"[SEP]": 102,
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"[UNK]": 100
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}
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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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"LABEL_99": 99
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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": "4.34.0",
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"vocab_size": 30522
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}
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pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:86a907d28a3fb965354cd88928199dd0e40fb45f0dafd9835e9431d5ff3cb2e7
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size 268156973
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special_tokens_map.json
ADDED
@@ -0,0 +1,7 @@
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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
ADDED
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tokenizer_config.json
ADDED
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [],
|
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"clean_up_tokenization_spaces": true,
|
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"cls_token": "[CLS]",
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"do_lower_case": true,
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48 |
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"mask_token": "[MASK]",
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49 |
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"model_max_length": 512,
|
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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52 |
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"strip_accents": null,
|
53 |
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"tokenize_chinese_chars": true,
|
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"tokenizer_class": "DistilBertTokenizer",
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55 |
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"unk_token": "[UNK]"
|
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}
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:630e00b46d6b08aa173bd734f0e77dd6ffb7113afae3b2893e596504585dc5ea
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size 4091
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vocab.txt
ADDED
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