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prompt_fine_tuned_boolq_bert

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tjasad/prompt_fine_tuned_boolq_bert

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Files changed (12) hide show
  1. README.md +14 -10
  2. adapter_config.json +17 -0
  3. adapter_model.safetensors +3 -0
  4. runs/May03_08-24-34_53ae7b07d069/events.out.tfevents.1714724708.53ae7b07d069.855.2 +3 -0
  5. runs/May03_08-26-23_53ae7b07d069/events.out.tfevents.1714724789.53ae7b07d069.855.3 +3 -0
  6. runs/May03_08-27-10_53ae7b07d069/events.out.tfevents.1714724836.53ae7b07d069.855.4 +3 -0
  7. runs/May03_08-29-15_53ae7b07d069/events.out.tfevents.1714724964.53ae7b07d069.855.5 +3 -0
  8. runs/May03_08-30-29_53ae7b07d069/events.out.tfevents.1714725035.53ae7b07d069.855.6 +3 -0
  9. runs/May03_08-31-48_53ae7b07d069/events.out.tfevents.1714725114.53ae7b07d069.855.7 +3 -0
  10. runs/May03_08-33-51_53ae7b07d069/events.out.tfevents.1714725238.53ae7b07d069.855.8 +3 -0
  11. tokenizer.json +1 -1
  12. training_args.bin +1 -1
README.md CHANGED
@@ -1,8 +1,9 @@
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  ---
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  license: apache-2.0
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- base_model: google-bert/bert-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
@@ -18,7 +19,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6468
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  - Accuracy: 0.7778
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  - F1: 0.7481
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@@ -45,23 +46,26 @@ The following hyperparameters were used during training:
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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: 6
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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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- | No log | 1.0 | 12 | 0.6797 | 0.6667 | 0.6872 |
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- | No log | 2.0 | 24 | 0.6667 | 0.6667 | 0.6667 |
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- | No log | 3.0 | 36 | 0.6563 | 0.6667 | 0.6667 |
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- | No log | 4.0 | 48 | 0.6507 | 0.7222 | 0.7072 |
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- | No log | 5.0 | 60 | 0.6478 | 0.7222 | 0.7072 |
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- | No log | 6.0 | 72 | 0.6468 | 0.7778 | 0.7481 |
 
 
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  ### Framework versions
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  - Transformers 4.40.1
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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- - Tokenizers 0.19.1
 
1
  ---
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  license: apache-2.0
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+ library_name: peft
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  tags:
5
  - generated_from_trainer
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+ base_model: google-bert/bert-base-uncased
7
  metrics:
8
  - accuracy
9
  - f1
 
19
 
20
  This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.6710
23
  - Accuracy: 0.7778
24
  - F1: 0.7481
25
 
 
46
  - seed: 42
47
  - 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
52
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 12 | 0.7544 | 0.2222 | 0.0808 |
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+ | No log | 2.0 | 24 | 0.7285 | 0.2222 | 0.0808 |
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+ | No log | 3.0 | 36 | 0.7061 | 0.3333 | 0.2833 |
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+ | No log | 4.0 | 48 | 0.6909 | 0.5556 | 0.5926 |
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+ | No log | 5.0 | 60 | 0.6817 | 0.7222 | 0.7325 |
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+ | No log | 6.0 | 72 | 0.6760 | 0.7778 | 0.7778 |
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+ | No log | 7.0 | 84 | 0.6722 | 0.7778 | 0.7481 |
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+ | No log | 8.0 | 96 | 0.6710 | 0.7778 | 0.7481 |
63
 
64
 
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  ### Framework versions
66
 
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+ - PEFT 0.10.0
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  - Transformers 4.40.1
69
  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "num_layers": 6,
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+ "num_transformer_submodules": 1,
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+ "num_virtual_tokens": 12,
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+ "peft_type": "PROMPT_TUNING",
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+ "prompt_tuning_init": "RANDOM",
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