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JudeChaer
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fire_or_not

Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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JudeChaer commited on
Commit
9198335
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verified ·
1 Parent(s): a18b320

End of training

Browse files
Files changed (6) hide show
  1. README.md +7 -4
  2. config.json +1 -1
  3. logs/events.out.tfevents.1709814002.mintj.8651.0 +3 -0
  4. logs/events.out.tfevents.1709814211.mintj.8651.1 +3 -0
  5. model.safetensors +1 -1
  6. training_args.bin +1 -1
README.md CHANGED
@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.4707
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  ## Model description
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@@ -39,14 +39,17 @@ The following hyperparameters were used during training:
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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: 500
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- - num_epochs: 2
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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 | 4 | 3.6174 |
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- | No log | 2.0 | 8 | 3.4707 |
 
 
 
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  ### Framework versions
 
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.0228
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  ## Model description
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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: 500
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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 | 4 | 3.1650 |
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+ | No log | 2.0 | 8 | 3.0043 |
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+ | 2.3478 | 3.0 | 12 | 2.7466 |
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+ | 2.3478 | 4.0 | 16 | 2.4101 |
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+ | 1.7944 | 5.0 | 20 | 2.0228 |
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  ### Framework versions
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "JudeChaer/fires",
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  "architectures": [
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  "RobertaForSequenceClassification"
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  ],
 
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  {
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+ "_name_or_path": "JudeChaer/fire_or_not",
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  "architectures": [
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  "RobertaForSequenceClassification"
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  ],
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