abdulelahagr
commited on
Commit
•
bf3d770
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Parent(s):
ac0f211
initial commit
Browse files- README.md +88 -0
- all_results.json +13 -0
- config.json +32 -0
- eval_results.json +8 -0
- model.safetensors +3 -0
- preprocessor_config.json +36 -0
- runs/Apr22_18-43-01_7118ffc10d0b/events.out.tfevents.1713811381.7118ffc10d0b.14620.0 +3 -0
- runs/Apr22_18-43-01_7118ffc10d0b/events.out.tfevents.1713812995.7118ffc10d0b.14620.1 +3 -0
- train_results.json +8 -0
- trainer_state.json +2442 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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---
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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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metrics:
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- accuracy
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model-index:
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- name: vit-base-chest-xray
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results: []
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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-chest-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: 0.0856
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- Accuracy: 0.9742
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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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| 0.1891 | 0.1307 | 100 | 0.1028 | 0.9665 |
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| 0.2123 | 0.2614 | 200 | 0.1254 | 0.9562 |
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| 0.0536 | 0.3922 | 300 | 0.1142 | 0.9691 |
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| 0.0799 | 0.5229 | 400 | 0.1173 | 0.9648 |
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| 0.0537 | 0.6536 | 500 | 0.0856 | 0.9742 |
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| 0.0911 | 0.7843 | 600 | 0.2005 | 0.9425 |
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| 0.1027 | 0.9150 | 700 | 0.0869 | 0.9708 |
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| 0.1011 | 1.0458 | 800 | 0.1063 | 0.9631 |
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| 0.0717 | 1.1765 | 900 | 0.1424 | 0.9588 |
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| 0.0605 | 1.3072 | 1000 | 0.1525 | 0.9648 |
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| 0.0573 | 1.4379 | 1100 | 0.0970 | 0.9700 |
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| 0.024 | 1.5686 | 1200 | 0.0867 | 0.9751 |
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| 0.0056 | 1.6993 | 1300 | 0.0888 | 0.9760 |
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| 0.0051 | 1.8301 | 1400 | 0.1054 | 0.9768 |
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| 0.063 | 1.9608 | 1500 | 0.1896 | 0.9571 |
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| 0.002 | 2.0915 | 1600 | 0.1886 | 0.9588 |
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| 0.005 | 2.2222 | 1700 | 0.1184 | 0.9734 |
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| 0.0083 | 2.3529 | 1800 | 0.1084 | 0.9760 |
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| 0.0013 | 2.4837 | 1900 | 0.0903 | 0.9777 |
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| 0.0298 | 2.6144 | 2000 | 0.1023 | 0.9734 |
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| 0.0008 | 2.7451 | 2100 | 0.1104 | 0.9768 |
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| 0.0011 | 2.8758 | 2200 | 0.1128 | 0.9785 |
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| 0.0006 | 3.0065 | 2300 | 0.1395 | 0.9734 |
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| 0.0059 | 3.1373 | 2400 | 0.1419 | 0.9725 |
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| 0.0005 | 3.2680 | 2500 | 0.1335 | 0.9777 |
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| 0.0005 | 3.3987 | 2600 | 0.1249 | 0.9768 |
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| 0.0007 | 3.5294 | 2700 | 0.1157 | 0.9777 |
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| 0.0005 | 3.6601 | 2800 | 0.1202 | 0.9785 |
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| 0.001 | 3.7908 | 2900 | 0.1239 | 0.9777 |
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| 0.0004 | 3.9216 | 3000 | 0.1231 | 0.9768 |
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### Framework versions
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- Transformers 4.40.0
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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": 0.9742489270386266,
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"eval_loss": 0.08559587597846985,
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"eval_runtime": 15.5649,
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"eval_samples_per_second": 74.848,
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"eval_steps_per_second": 9.38,
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"total_flos": 3.7909081319458406e+18,
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"train_loss": 0.047429592626662374,
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"train_runtime": 1590.6048,
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"train_samples_per_second": 30.756,
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"train_steps_per_second": 1.924
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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": "PNEUMONIA",
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"1": "NORMAL"
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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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"NORMAL": "1",
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"PNEUMONIA": "0"
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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": "4.40.0"
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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": 0.9742489270386266,
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"eval_loss": 0.08559587597846985,
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"eval_runtime": 15.5649,
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"eval_samples_per_second": 74.848,
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"eval_steps_per_second": 9.38
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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:b9bcb42bee7381aa20ffba641ad5e9ae2b83011862860f9bc5729090cdcefae1
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size 343223968
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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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}
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runs/Apr22_18-43-01_7118ffc10d0b/events.out.tfevents.1713811381.7118ffc10d0b.14620.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:a718059f0a2c96b3fc39481dec5dc4ff8cfe0e9bb7e19d0bdd9dd58078fa10a1
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size 79238
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runs/Apr22_18-43-01_7118ffc10d0b/events.out.tfevents.1713812995.7118ffc10d0b.14620.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:ae1b2bae53d20332f2c057b673006991ff3c5a6a35d6b84d71708b4c6a7a1301
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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": 3.7909081319458406e+18,
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"train_loss": 0.047429592626662374,
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+
"train_runtime": 1590.6048,
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"train_samples_per_second": 30.756,
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"train_steps_per_second": 1.924
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}
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trainer_state.json
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