End of training
Browse files- README.md +66 -0
- config.json +33 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: albert-base-v2
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tags:
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- generated_from_trainer
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datasets:
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- squad
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model-index:
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- name: cs4248_albert-base-v2_bilstm_qa
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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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# cs4248_albert-base-v2_bilstm_qa
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the squad dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.9086
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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: 8
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- eval_batch_size: 8
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- seed: 4248
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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: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 4.4082 | 1.0 | 500 | 4.4031 |
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| 3.951 | 2.0 | 1000 | 4.3329 |
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| 3.6099 | 3.0 | 1500 | 4.3608 |
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| 3.3651 | 4.0 | 2000 | 4.4929 |
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| 3.0356 | 5.0 | 2500 | 4.5390 |
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| 2.8111 | 6.0 | 3000 | 4.7661 |
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| 2.5587 | 7.0 | 3500 | 4.8550 |
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| 2.4021 | 8.0 | 4000 | 4.9086 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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config.json
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{
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"_name_or_path": "albert-base-v2",
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"architectures": [
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"PreTrainedWithBiLSTM"
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],
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"attention_probs_dropout_prob": 0,
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"bos_token_id": 2,
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"classifier_dropout_prob": 0.1,
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"down_scale_factor": 1,
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"embedding_size": 128,
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"eos_token_id": 3,
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"gap_size": 0,
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"hidden_act": "gelu_new",
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"hidden_dropout_prob": 0,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"inner_group_num": 1,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "albert",
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"net_structure_type": 0,
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"num_attention_heads": 12,
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"num_hidden_groups": 1,
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"num_hidden_layers": 12,
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"num_memory_blocks": 0,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.34.1",
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"type_vocab_size": 2,
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"vocab_size": 30000
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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 sha256:88e7b7c7ade7cea9a013c38e193119a2a86e570e230093d4482c59afc0d35076
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size 52791356
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special_tokens_map.json
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{
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"eos_token": "[SEP]",
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"mask_token": {
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"content": "[MASK]",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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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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"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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"1": {
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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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"2": {
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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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"3": {
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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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"4": {
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"content": "[MASK]",
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"lstrip": true,
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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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"bos_token": "[CLS]",
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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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"eos_token": "[SEP]",
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"keep_accents": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "<pad>",
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"remove_space": true,
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"sep_token": "[SEP]",
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"tokenizer_class": "AlbertTokenizer",
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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:e65b66dcf0a8231878fc53740f4fd2a26b659720c80d3dea0bd67db512b899ec
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size 4536
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