Commit
•
f37dd19
1
Parent(s):
5804c40
initial commit
Browse files- README.md +83 -0
- all_results.json +13 -0
- config.json +36 -0
- eval_results.json +8 -0
- model.safetensors +3 -0
- preprocessor_config.json +36 -0
- runs/Apr26_22-27-12_281779fe3e77/events.out.tfevents.1714170432.281779fe3e77.1775.0 +3 -0
- runs/Apr26_22-27-12_281779fe3e77/events.out.tfevents.1714171146.281779fe3e77.1775.1 +3 -0
- train_results.json +8 -0
- trainer_state.json +597 -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: google/vit-base-patch16-224-in21k
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tags:
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- image-classification
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: vit-base-brain-xray
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: trpakov/chest-xray-classification
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type: imagefolder
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config: default
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split: Testing
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.748730964467005
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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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# vit-base-brain-xray
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the trpakov/chest-xray-classification dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8358
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- Accuracy: 0.7487
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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: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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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: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.2744 | 0.5556 | 100 | 0.8358 | 0.7487 |
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| 0.1827 | 1.1111 | 200 | 1.0390 | 0.7538 |
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| 0.1388 | 1.6667 | 300 | 1.1603 | 0.7563 |
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| 0.0317 | 2.2222 | 400 | 1.2382 | 0.7538 |
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| 0.0144 | 2.7778 | 500 | 1.2834 | 0.7513 |
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| 0.0062 | 3.3333 | 600 | 1.3673 | 0.7563 |
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| 0.0257 | 3.8889 | 700 | 1.2926 | 0.7665 |
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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
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all_results.json
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{
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"epoch": 4.0,
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"eval_accuracy": 0.748730964467005,
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"eval_loss": 0.835834801197052,
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"eval_runtime": 6.8785,
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"eval_samples_per_second": 57.28,
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"eval_steps_per_second": 7.269,
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"total_flos": 8.896239873264845e+17,
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"train_loss": 0.14669639009775387,
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"train_runtime": 706.4893,
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"train_samples_per_second": 16.249,
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"train_steps_per_second": 1.019
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}
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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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": 768,
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"id2label": {
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"0": "glioma_tumor",
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"1": "meningioma_tumor",
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"2": "no_tumor",
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"3": "pituitary_tumor"
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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": 3072,
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"label2id": {
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"glioma_tumor": "0",
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"meningioma_tumor": "1",
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"no_tumor": "2",
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"pituitary_tumor": "3"
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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": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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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": "4.40.1"
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}
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eval_results.json
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{
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"epoch": 4.0,
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"eval_accuracy": 0.748730964467005,
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"eval_loss": 0.835834801197052,
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| 5 |
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"eval_runtime": 6.8785,
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"eval_samples_per_second": 57.28,
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"eval_steps_per_second": 7.269
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:864dda7ffb7fb28c594efd1d1671a5b679121dc9f6e3bdee84cd3d6ab4f0b2e9
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size 343230128
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preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"do_resize",
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"size",
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"resample",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"return_tensors",
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"data_format",
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"input_data_format"
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],
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTImageProcessor",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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| 36 |
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}
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runs/Apr26_22-27-12_281779fe3e77/events.out.tfevents.1714170432.281779fe3e77.1775.0
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:057c9366dd4a69ff011d7c437536cf4dc472686e8f7499cddefac5f0b34033f7
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| 3 |
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size 22559
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runs/Apr26_22-27-12_281779fe3e77/events.out.tfevents.1714171146.281779fe3e77.1775.1
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:dbb72bb1e131951043ea31606efd06da4301ac45a664dd6a8f11ba272e194c77
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size 411
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train_results.json
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{
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"epoch": 4.0,
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"total_flos": 8.896239873264845e+17,
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"train_loss": 0.14669639009775387,
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| 5 |
+
"train_runtime": 706.4893,
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| 6 |
+
"train_samples_per_second": 16.249,
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| 7 |
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"train_steps_per_second": 1.019
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| 8 |
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}
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trainer_state.json
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|
| 596 |
+
"trial_params": null
|
| 597 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0e85701c3785f8f1bd6b77fa9240d0634e81af7e955718efcc7ad98aaae9d642
|
| 3 |
+
size 4984
|