Commit
•
4cbc492
1
Parent(s):
f2b71b2
Yayyy Lets Share hateful Memes!!!
Browse files- README.md +70 -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/Apr10_11-12-24_decc3680cd07/events.out.tfevents.1712747583.decc3680cd07.703.0 +3 -0
- runs/Apr10_11-12-24_decc3680cd07/events.out.tfevents.1712748254.decc3680cd07.703.1 +3 -0
- runs/Apr10_11-28-52_decc3680cd07/events.out.tfevents.1712748567.decc3680cd07.703.2 +3 -0
- runs/Apr10_11-28-52_decc3680cd07/events.out.tfevents.1712749961.decc3680cd07.703.3 +3 -0
- train_results.json +8 -0
- trainer_state.json +3077 -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
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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-hate-meme
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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-hate-meme
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the emily49/hateful_memes_train_dev dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7461
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- Accuracy: 0.498
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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: 32
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 8
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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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| 0.6483 | 1.0 | 532 | 0.7933 | 0.5 |
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| 0.6203 | 2.0 | 1064 | 0.7461 | 0.498 |
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| 0.5955 | 3.0 | 1596 | 0.7539 | 0.518 |
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| 0.4796 | 4.0 | 2128 | 0.9387 | 0.536 |
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| 0.425 | 5.0 | 2660 | 0.9824 | 0.538 |
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| 0.2869 | 6.0 | 3192 | 1.6186 | 0.542 |
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| 0.0337 | 7.0 | 3724 | 2.5670 | 0.538 |
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| 0.0166 | 8.0 | 4256 | 2.8061 | 0.538 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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all_results.json
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{
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"epoch": 8.0,
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"eval_accuracy": 0.498,
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"eval_loss": 0.746105968952179,
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"eval_runtime": 5.5949,
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"eval_samples_per_second": 89.367,
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"eval_steps_per_second": 2.86,
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"total_flos": 5.269455293792256e+18,
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"train_loss": 0.40350076897398923,
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"train_runtime": 1386.2467,
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"train_samples_per_second": 49.053,
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"train_steps_per_second": 3.07
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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",
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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": 0,
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"1": 1
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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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"0": "0",
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"1": "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": 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": "4.39.3"
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}
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eval_results.json
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{
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"epoch": 8.0,
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"eval_accuracy": 0.498,
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"eval_loss": 0.746105968952179,
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"eval_runtime": 5.5949,
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"eval_samples_per_second": 89.367,
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"eval_steps_per_second": 2.86
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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:e8710ba864bae83388e22f3b5e1f0c884776b615f25c94f15cc3b917142ee7cd
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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/Apr10_11-12-24_decc3680cd07/events.out.tfevents.1712747583.decc3680cd07.703.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:9a011c4bbc10c6dbcabde2d519d8dd8e46e8fed5e7f235be6a03a4f1f9167c09
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size 17683
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runs/Apr10_11-12-24_decc3680cd07/events.out.tfevents.1712748254.decc3680cd07.703.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:7c5a5acc663006d4f4fb7a1e1628f3b8737def1c2dd1e8ef679c731785b7a7c2
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size 411
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runs/Apr10_11-28-52_decc3680cd07/events.out.tfevents.1712748567.decc3680cd07.703.2
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version https://git-lfs.github.com/spec/v1
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size 97231
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runs/Apr10_11-28-52_decc3680cd07/events.out.tfevents.1712749961.decc3680cd07.703.3
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version https://git-lfs.github.com/spec/v1
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oid sha256:48fa56668bf4f481f9001ec1c3d4156d5ee4238f2e1bb620f9c97dc4a195f027
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size 411
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train_results.json
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{
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"epoch": 8.0,
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"total_flos": 5.269455293792256e+18,
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"train_loss": 0.40350076897398923,
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"train_runtime": 1386.2467,
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"train_samples_per_second": 49.053,
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"train_steps_per_second": 3.07
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}
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trainer_state.json
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|
1 |
+
{
|
2 |
+
"best_metric": 0.746105968952179,
|
3 |
+
"best_model_checkpoint": "./vit-base-hate-meme/checkpoint-1064",
|
4 |
+
"epoch": 8.0,
|
5 |
+
"eval_steps": 500,
|
6 |
+
"global_step": 4256,
|
7 |
+
"is_hyper_param_search": false,
|
8 |
+
"is_local_process_zero": true,
|
9 |
+
"is_world_process_zero": true,
|
10 |
+
"log_history": [
|
11 |
+
{
|
12 |
+
"epoch": 0.02,
|
13 |
+
"grad_norm": 1.893226146697998,
|
14 |
+
"learning_rate": 3.6e-06,
|
15 |
+
"loss": 0.6079,
|
16 |
+
"step": 10
|
17 |
+
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