End of training
Browse files- README.md +28 -29
- all_results.json +20 -20
- config.json +6 -6
- eval_results.json +15 -15
- model.safetensors +2 -2
- runs/Feb02_21-20-23_modal/events.out.tfevents.1738531224.modal.2.0 +3 -0
- runs/Feb02_21-20-23_modal/events.out.tfevents.1738531224.modal.2.1 +3 -0
- runs/Feb02_21-20-23_modal/events.out.tfevents.1738531733.modal.2.2 +3 -0
- runs/Feb02_21-20-23_modal/events.out.tfevents.1738531733.modal.2.3 +3 -0
- train_results.json +6 -6
- trainer_state.json +567 -690
- training_args.bin +1 -1
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google/vit-
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tags:
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- generated_from_trainer
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metrics:
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# squarerun_earlystop
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This model is a fine-tuned version of [google/vit-
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- F1 Macro: 0.
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- F1 Micro: 0.
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- F1 Weighted: 0.
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- Precision Macro: 0.
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- Precision Micro: 0.
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- Precision Weighted: 0.
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- Recall Macro: 0.
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- Recall Micro: 0.
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- Recall Weighted: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
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| 0.8642 | 14.0 | 406 | 1.1884 | 0.5114 | 0.5985 | 0.5884 | 0.5284 | 0.5985 | 0.6108 | 0.5244 | 0.5985 | 0.5985 | 0.5985 |
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### Framework versions
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- Transformers 4.48.
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- Pytorch 2.
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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---
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library_name: transformers
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license: apache-2.0
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base_model: google/vit-large-patch16-224
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tags:
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- generated_from_trainer
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metrics:
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# squarerun_earlystop
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This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2750
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- F1 Macro: 0.4568
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- F1 Micro: 0.5455
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- F1 Weighted: 0.5111
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- Precision Macro: 0.4686
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- Precision Micro: 0.5455
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- Precision Weighted: 0.5173
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- Recall Macro: 0.4845
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- Recall Micro: 0.5455
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- Recall Weighted: 0.5455
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- Accuracy: 0.5455
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
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| 1.9437 | 1.0 | 29 | 1.8987 | 0.1485 | 0.2576 | 0.1680 | 0.1192 | 0.2576 | 0.1321 | 0.2207 | 0.2576 | 0.2576 | 0.2576 |
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| 1.4616 | 2.0 | 58 | 1.5844 | 0.3569 | 0.4242 | 0.4076 | 0.4336 | 0.4242 | 0.4738 | 0.3657 | 0.4242 | 0.4242 | 0.4242 |
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| 1.9935 | 3.0 | 87 | 1.4952 | 0.3059 | 0.4242 | 0.3585 | 0.3795 | 0.4242 | 0.4097 | 0.3387 | 0.4242 | 0.4242 | 0.4242 |
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| 1.3601 | 4.0 | 116 | 1.4319 | 0.3275 | 0.4167 | 0.3720 | 0.3223 | 0.4167 | 0.3618 | 0.3614 | 0.4167 | 0.4167 | 0.4167 |
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| 1.1685 | 5.0 | 145 | 1.1508 | 0.4913 | 0.5833 | 0.5550 | 0.4887 | 0.5833 | 0.5484 | 0.5139 | 0.5833 | 0.5833 | 0.5833 |
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| 1.2228 | 6.0 | 174 | 1.2663 | 0.4865 | 0.5076 | 0.5046 | 0.5339 | 0.5076 | 0.5644 | 0.4964 | 0.5076 | 0.5076 | 0.5076 |
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| 1.2811 | 7.0 | 203 | 1.4596 | 0.4084 | 0.5303 | 0.4752 | 0.5582 | 0.5303 | 0.6068 | 0.4383 | 0.5303 | 0.5303 | 0.5303 |
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| 1.7256 | 8.0 | 232 | 1.4908 | 0.4805 | 0.5682 | 0.5435 | 0.5333 | 0.5682 | 0.6122 | 0.5219 | 0.5682 | 0.5682 | 0.5682 |
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| 0.4549 | 9.0 | 261 | 1.2969 | 0.5270 | 0.6136 | 0.5648 | 0.6664 | 0.6136 | 0.6757 | 0.5526 | 0.6136 | 0.6136 | 0.6136 |
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| 0.5877 | 10.0 | 290 | 1.3581 | 0.4638 | 0.5758 | 0.5271 | 0.5632 | 0.5758 | 0.6293 | 0.5095 | 0.5758 | 0.5758 | 0.5758 |
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| 0.3451 | 11.0 | 319 | 1.2491 | 0.5613 | 0.6136 | 0.6066 | 0.5909 | 0.6136 | 0.6111 | 0.5589 | 0.6136 | 0.6136 | 0.6136 |
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| 0.4885 | 12.0 | 348 | 1.6862 | 0.5381 | 0.6288 | 0.6087 | 0.5515 | 0.6288 | 0.6225 | 0.5576 | 0.6288 | 0.6288 | 0.6288 |
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| 0.3835 | 13.0 | 377 | 1.8354 | 0.5318 | 0.5379 | 0.5440 | 0.6396 | 0.5379 | 0.6577 | 0.5264 | 0.5379 | 0.5379 | 0.5379 |
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### Framework versions
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- Transformers 4.48.2
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- Pytorch 2.6.0+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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all_results.json
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{
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"epoch":
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"eval_accuracy": 0.
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"eval_f1_macro": 0.
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"eval_f1_micro": 0.
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"eval_f1_weighted": 0.
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"eval_loss": 1.
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"eval_precision_macro": 0.
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"eval_precision_micro": 0.
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"eval_precision_weighted": 0.
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"eval_recall_macro": 0.
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"eval_recall_micro": 0.
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"eval_recall_weighted": 0.
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"eval_runtime": 1.
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"eval_samples_per_second":
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"eval_steps_per_second":
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"total_flos":
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"train_loss": 1.
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 2.
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}
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{
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"epoch": 13.0,
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"eval_runtime": 1.534,
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"eval_samples_per_second": 43.025,
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"eval_steps_per_second": 5.867,
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"total_flos": 1.6452764844550595e+18,
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"train_loss": 1.068754496403651,
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"train_runtime": 506.3845,
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"train_samples_per_second": 36.494,
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config.json
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{
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"_name_or_path": "google/vit-
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"architectures": [
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"ViTForImageClassification"
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],
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size":
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"id2label": {
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"0": "-",
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"1": "0",
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size":
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"label2id": {
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"0": "1",
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads":
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"num_channels": 3,
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"num_hidden_layers":
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.48.
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}
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{
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"_name_or_path": "google/vit-large-patch16-224",
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"architectures": [
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"ViTForImageClassification"
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],
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 1024,
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"id2label": {
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"0": "-",
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"1": "0",
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"-": "0",
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"0": "1",
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 16,
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"num_channels": 3,
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"num_hidden_layers": 24,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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eval_results.json
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model.safetensors
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train_results.json
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trainer_state.json
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{
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"best_metric": 1.
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"epoch":
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1569 |
}
|
| 1570 |
],
|
| 1571 |
"logging_steps": 2,
|
|
|
|
| 1576 |
"stateful_callbacks": {
|
| 1577 |
"EarlyStoppingCallback": {
|
| 1578 |
"args": {
|
| 1579 |
+
"early_stopping_patience": 8,
|
| 1580 |
"early_stopping_threshold": 0.0
|
| 1581 |
},
|
| 1582 |
"attributes": {
|
| 1583 |
+
"early_stopping_patience_counter": 8
|
| 1584 |
}
|
| 1585 |
},
|
| 1586 |
"TrainerControl": {
|
|
|
|
| 1594 |
"attributes": {}
|
| 1595 |
}
|
| 1596 |
},
|
| 1597 |
+
"total_flos": 1.6452764844550595e+18,
|
| 1598 |
"train_batch_size": 8,
|
| 1599 |
"trial_name": null,
|
| 1600 |
"trial_params": null
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5368
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3b2b32deb94bfd846b2c9efdfeba4bb55ba632e4f045fd94493f234b59c88c4b
|
| 3 |
size 5368
|