yourusername
commited on
Commit
•
ecf467c
1
Parent(s):
9c74c3a
add model
Browse files- .gitignore +1 -0
- README.md +76 -0
- all_results.json +12 -0
- config.json +32 -0
- emissions.csv +2 -0
- eval_results.json +8 -0
- preprocessor_config.json +17 -0
- pytorch_model.bin +3 -0
- runs/Aug31_12-52-34_nate-gpu-2/1630414364.999114/events.out.tfevents.1630414364.nate-gpu-2.12898.1 +3 -0
- runs/Aug31_12-52-34_nate-gpu-2/events.out.tfevents.1630414364.nate-gpu-2.12898.0 +3 -0
- runs/Aug31_12-52-34_nate-gpu-2/events.out.tfevents.1630414491.nate-gpu-2.12898.2 +3 -0
- train_results.json +7 -0
- trainer_state.json +460 -0
- training_args.bin +3 -0
.gitignore
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checkpoint-*/
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- beans
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metrics:
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- accuracy
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model-index:
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- name: vit-base-beans
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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: beans
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type: beans
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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: 0.9774436090225563
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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-beans
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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 beans dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0942
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- Accuracy: 0.9774
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 1337
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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: 5.0
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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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| 0.2809 | 1.0 | 130 | 0.2287 | 0.9699 |
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| 0.1097 | 2.0 | 260 | 0.1676 | 0.9624 |
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| 0.1027 | 3.0 | 390 | 0.0942 | 0.9774 |
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| 0.0923 | 4.0 | 520 | 0.1104 | 0.9699 |
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| 0.1726 | 5.0 | 650 | 0.1030 | 0.9699 |
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### Framework versions
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- Transformers 4.10.0.dev0
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- Pytorch 1.9.0+cu102
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- Datasets 1.11.1.dev0
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- Tokenizers 0.10.3
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all_results.json
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{
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"epoch": 5.0,
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"eval_accuracy": 0.9774436090225563,
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"eval_loss": 0.09423530101776123,
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"eval_runtime": 1.7062,
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"eval_samples_per_second": 77.951,
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"eval_steps_per_second": 9.964,
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"train_loss": 0.23702784006412211,
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"train_runtime": 124.7505,
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"train_samples_per_second": 41.443,
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"train_steps_per_second": 5.21
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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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"finetuning_task": "image-classification",
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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": "angular_leaf_spot",
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"1": "bean_rust",
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"2": "healthy"
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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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"angular_leaf_spot": "0",
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"bean_rust": "1",
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"healthy": "2"
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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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"torch_dtype": "float32",
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"transformers_version": "4.10.0.dev0"
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}
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emissions.csv
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timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region
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2021-08-31T12:54:49,a4449492-67ee-4738-a85d-5ac4861bcb29,codecarbon,124.76043105125427,0.005462426324374648,0.009645817277723201,USA,USA,Iowa,Y,gcp,us-central1
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eval_results.json
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{
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"epoch": 5.0,
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"eval_accuracy": 0.9774436090225563,
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"eval_loss": 0.09423530101776123,
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+
"eval_runtime": 1.7062,
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"eval_samples_per_second": 77.951,
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"eval_steps_per_second": 9.964
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}
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ViTFeatureExtractor",
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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_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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"size": 224
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:fc443b145fcc3a09cf07eb28b94e9a989ec3f0e8f7255e1fa08c0953ed4bae91
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size 343282929
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runs/Aug31_12-52-34_nate-gpu-2/1630414364.999114/events.out.tfevents.1630414364.nate-gpu-2.12898.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:0518be0bbb187145974df13bed88d402be8eb609cabf1527c4a09df057b7a1ef
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size 4216
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runs/Aug31_12-52-34_nate-gpu-2/events.out.tfevents.1630414364.nate-gpu-2.12898.0
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:d838680fe881c3f25f235ece74982927b314f580b29d1224c44a3df042bd64b4
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size 15187
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runs/Aug31_12-52-34_nate-gpu-2/events.out.tfevents.1630414491.nate-gpu-2.12898.2
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version https://git-lfs.github.com/spec/v1
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oid sha256:8aaee3d3e039b4a6e840ad05b41b11c749918c7925d1c19fa4524e0423d179d7
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size 363
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train_results.json
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{
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"epoch": 5.0,
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"train_loss": 0.23702784006412211,
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"train_runtime": 124.7505,
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"train_samples_per_second": 41.443,
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"train_steps_per_second": 5.21
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}
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trainer_state.json
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{
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"best_metric": 0.09423530101776123,
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"best_model_checkpoint": "./beans_outputs/checkpoint-390",
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"epoch": 5.0,
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"eval_loss": 0.10300374776124954,
|
440 |
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"eval_runtime": 1.6531,
|
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"eval_samples_per_second": 80.453,
|
442 |
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"eval_steps_per_second": 10.284,
|
443 |
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"step": 650
|
444 |
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},
|
445 |
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{
|
446 |
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"epoch": 5.0,
|
447 |
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"step": 650,
|
448 |
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"total_flos": 0.0,
|
449 |
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"train_loss": 0.23702784006412211,
|
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"train_runtime": 124.7505,
|
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"train_samples_per_second": 41.443,
|
452 |
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"train_steps_per_second": 5.21
|
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}
|
454 |
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],
|
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"max_steps": 650,
|
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"num_train_epochs": 5,
|
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"total_flos": 0.0,
|
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"trial_name": null,
|
459 |
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"trial_params": null
|
460 |
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}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:dbfebeca32be1d102a71d29619d0db0783df335f73af946dd488cfac20c644ec
|
3 |
+
size 2671
|