Commit
•
6105845
1
Parent(s):
e34ed1f
initialize model repository
Browse files- README.md +55 -1
- all_results.json +15 -0
- config.json +47 -0
- eval_results.json +10 -0
- generation_config.json +5 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +15 -0
- trainer_state.json +3472 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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-
license:
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---
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| 1 |
---
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license: mit
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base_model: indobenchmark/indobert-large-p2
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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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model-index:
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- name: out
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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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# out
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This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6595
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- Accuracy: 0.6803
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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: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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: 3.0
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### Training results
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.13.3
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all_results.json
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{
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"epoch": 3.0,
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"eval_accuracy": 0.680344407644915,
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"eval_loss": 1.6595289707183838,
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"eval_runtime": 118.3166,
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"eval_samples": 18002,
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"eval_samples_per_second": 152.151,
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"eval_steps_per_second": 19.025,
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"perplexity": 5.256834138384373,
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"train_loss": 2.060935147813305,
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"train_runtime": 51665.6711,
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"train_samples": 765530,
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"train_samples_per_second": 44.451,
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"train_steps_per_second": 5.556
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}
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config.json
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{
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"_name_or_path": "indobenchmark/indobert-large-p2",
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"_num_labels": 5,
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"architectures": [
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"BertForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"directionality": "bidi",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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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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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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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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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"output_past": true,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.33.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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eval_results.json
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{
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"epoch": 3.0,
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"eval_accuracy": 0.680344407644915,
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"eval_loss": 1.6595289707183838,
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"eval_runtime": 118.3166,
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"eval_samples": 18002,
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"eval_samples_per_second": 152.151,
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"eval_steps_per_second": 19.025,
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"perplexity": 5.256834138384373
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}
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generation_config.json
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{
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"_from_model_config": true,
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"pad_token_id": 0,
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"transformers_version": "4.33.1"
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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 sha256:76b96f733918c43e9596b290cf75f66fe86dd7fa0d2ecaba76b0beaed204705d
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size 1340833266
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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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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 1000000000000000019884624838656,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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trainer_state.json
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vocab.txt
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