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Browse files- LICENSE +21 -0
- README.md +69 -0
- all_results.json +23 -0
- config.json +33 -0
- eval_results.json +11 -0
- model.safetensors +3 -0
- preprocessor_config.json +13 -0
- test_results.json +11 -0
- train_results.json +7 -0
- trainer_state.json +1128 -0
- training_args.bin +3 -0
LICENSE
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MIT License
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Copyright (c) 2024 The Alan Turing Institute
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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license: mit
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---
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---
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license: mit
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base_model: MIT/ast-finetuned-audioset-10-10-0.4593
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: AST-VoxCelebSpoof-Synthetic-Voice-Detection
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results: []
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datasets:
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- MattyB95/VoxCelebSpoof
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language:
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- en
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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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# AST-VoxCelebSpoof-Synthetic-Voice-Detection
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This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 89136693248.0
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- Accuracy: 0.9999
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- F1: 0.9999
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- Precision: 1.0
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- Recall: 0.9998
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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: 5e-05
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- train_batch_size: 8
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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: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-----------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 2218896740319.232 | 1.0 | 29527 | 611463921664.0 | 0.9998 | 0.9998 | 0.9999 | 0.9997 |
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| 522149441830.912 | 2.0 | 59054 | 284563668992.0 | 0.9997 | 0.9997 | 0.9999 | 0.9996 |
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| 0.0 | 3.0 | 88581 | 89136693248.0 | 0.9999 | 0.9999 | 1.0 | 0.9998 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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all_results.json
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{
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"Test_accuracy": 0.9998475958241256,
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"Test_f1": 0.9998758483694752,
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"Test_loss": 123070660608.0,
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"Test_precision": 0.9999793059205762,
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"Test_recall": 0.9997724122235325,
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"Test_runtime": 5135.0444,
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"Test_samples_per_second": 15.333,
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"Test_steps_per_second": 1.917,
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"Validation_accuracy": 0.9998856954163862,
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"Validation_f1": 0.9999061434336903,
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"Validation_loss": 89136693248.0,
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"Validation_precision": 1.0,
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"Validation_recall": 0.9998123044838373,
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"Validation_runtime": 5062.7566,
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"Validation_samples_per_second": 15.552,
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"Validation_steps_per_second": 1.944,
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"epoch": 3.0,
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"train_loss": 10893808030881.182,
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"train_runtime": 445813.7666,
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"train_samples_per_second": 1.59,
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"train_steps_per_second": 0.199
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}
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config.json
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{
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"_name_or_path": "MIT/ast-finetuned-audioset-10-10-0.4593",
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"architectures": [
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"ASTForAudioClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"frequency_stride": 10,
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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": "Bonafide",
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"1": "Spoof"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Bonafide": "0",
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"Spoof": "1"
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},
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"layer_norm_eps": 1e-12,
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"max_length": 1024,
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"model_type": "audio-spectrogram-transformer",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"num_mel_bins": 128,
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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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"time_stride": 10,
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"torch_dtype": "float32",
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"transformers_version": "4.36.2"
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}
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eval_results.json
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{
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"Validation_accuracy": 0.9998856954163862,
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"Validation_f1": 0.9999061434336903,
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"Validation_loss": 89136693248.0,
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+
"Validation_precision": 1.0,
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"Validation_recall": 0.9998123044838373,
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"Validation_runtime": 5062.7566,
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"Validation_samples_per_second": 15.552,
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"Validation_steps_per_second": 1.944,
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"epoch": 3.0
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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 sha256:22f60e485112e04c008e9a586aad9d49ae2f77bcd6714335fcb75e3cf4721c57
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size 344790040
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preprocessor_config.json
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{
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"do_normalize": true,
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"feature_extractor_type": "ASTFeatureExtractor",
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"feature_size": 1,
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"max_length": 1024,
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"mean": -4.2677393,
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"num_mel_bins": 128,
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"padding_side": "right",
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"padding_value": 0.0,
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"return_attention_mask": false,
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"sampling_rate": 16000,
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"std": 4.5689974
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}
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test_results.json
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{
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"Test_accuracy": 0.9998475958241256,
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"Test_f1": 0.9998758483694752,
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+
"Test_loss": 123070660608.0,
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+
"Test_precision": 0.9999793059205762,
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+
"Test_recall": 0.9997724122235325,
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+
"Test_runtime": 5135.0444,
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+
"Test_samples_per_second": 15.333,
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"Test_steps_per_second": 1.917,
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"epoch": 3.0
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}
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train_results.json
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{
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"epoch": 3.0,
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"train_loss": 10893808030881.182,
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+
"train_runtime": 445813.7666,
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+
"train_samples_per_second": 1.59,
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"train_steps_per_second": 0.199
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}
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trainer_state.json
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@@ -0,0 +1,3 @@
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