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roberta-base_correlation

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Nared45/roberta-base_correlation

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  1. README.md +16 -31
  2. config.json +2 -6
  3. logs/events.out.tfevents.1725506043.ip-172-16-38-49.ap-southeast-1.compute.internal.10329.4 +3 -0
  4. model.safetensors +1 -1
  5. training_args.bin +2 -2
README.md CHANGED
@@ -1,6 +1,7 @@
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  ---
 
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  license: mit
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- base_model: roberta-base
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -13,9 +14,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # roberta-base_correlation
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- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4129
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  ## Model description
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@@ -34,44 +35,28 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 32
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- - eval_batch_size: 16
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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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- - lr_scheduler_warmup_steps: 5000
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- - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6673 | 1.0 | 50 | 0.6690 |
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- | 0.6707 | 2.0 | 100 | 0.6668 |
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- | 0.6593 | 3.0 | 150 | 0.6631 |
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- | 0.6597 | 4.0 | 200 | 0.6583 |
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- | 0.6476 | 5.0 | 250 | 0.6536 |
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- | 0.6511 | 6.0 | 300 | 0.6487 |
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- | 0.6342 | 7.0 | 350 | 0.6459 |
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- | 0.6408 | 8.0 | 400 | 0.6427 |
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- | 0.6318 | 9.0 | 450 | 0.6405 |
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- | 0.6556 | 10.0 | 500 | 0.6372 |
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- | 0.6141 | 11.0 | 550 | 0.6289 |
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- | 0.59 | 12.0 | 600 | 0.6089 |
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- | 0.5781 | 13.0 | 650 | 0.5815 |
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- | 0.5529 | 14.0 | 700 | 0.5550 |
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- | 0.5367 | 15.0 | 750 | 0.5355 |
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- | 0.5107 | 16.0 | 800 | 0.5014 |
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- | 0.4441 | 17.0 | 850 | 0.4775 |
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- | 0.4206 | 18.0 | 900 | 0.4477 |
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- | 0.3608 | 19.0 | 950 | 0.4302 |
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- | 0.3241 | 20.0 | 1000 | 0.4129 |
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  ### Framework versions
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- - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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- - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  ---
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+ library_name: transformers
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  license: mit
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+ base_model: FacebookAI/roberta-base
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # roberta-base_correlation
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7933
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  ## Model description
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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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  - 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: 5
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 78 | 0.5864 |
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+ | No log | 2.0 | 156 | 0.4928 |
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+ | No log | 3.0 | 234 | 0.5737 |
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+ | No log | 4.0 | 312 | 0.8163 |
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+ | No log | 5.0 | 390 | 0.7933 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.44.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "roberta-base",
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  "architectures": [
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  "RobertaForSequenceClassification"
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  ],
@@ -10,10 +10,6 @@
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  "hidden_act": "gelu",
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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- "id2label": {
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- "0": 0,
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- "1": 1
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- },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "layer_norm_eps": 1e-05,
@@ -25,7 +21,7 @@
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.38.2",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 50265
 
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  {
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+ "_name_or_path": "FacebookAI/roberta-base",
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  "architectures": [
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  "RobertaForSequenceClassification"
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  ],
 
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  "hidden_act": "gelu",
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
 
 
 
 
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "layer_norm_eps": 1e-05,
 
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.44.2",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 50265
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