Instructions to use Devishetty100/redmoon-gibberishdetective with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devishetty100/redmoon-gibberishdetective with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Devishetty100/redmoon-gibberishdetective")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Devishetty100/redmoon-gibberishdetective") model = AutoModelForSequenceClassification.from_pretrained("Devishetty100/redmoon-gibberishdetective") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1, checkpoint
Browse files- checkpoint-95/config.json +33 -0
- checkpoint-95/model.safetensors +3 -0
- checkpoint-95/optimizer.pt +3 -0
- checkpoint-95/rng_state.pth +3 -0
- checkpoint-95/scaler.pt +3 -0
- checkpoint-95/scheduler.pt +3 -0
- checkpoint-95/trainer_state.json +42 -0
- checkpoint-95/training_args.bin +3 -0
checkpoint-95/config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "clean",
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"1": "gibberish"
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},
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"initializer_range": 0.02,
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"label2id": {
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"clean": 0,
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"gibberish": 1
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.49.0",
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"vocab_size": 30522
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}
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checkpoint-95/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6676c1b143c8ccfa558a4f96868afc7e7e66d73c99b29d43caa266b664196fb9
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size 267832560
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checkpoint-95/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:f29472fc6644fb96b1063de90afb4e5f97b20e9eff487ff33d06dec5ddae0a89
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size 535727290
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checkpoint-95/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:9c16bad3a5ef45420da273943dddc8a1b9c2e918783152a7d6935d6230b34394
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size 14244
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checkpoint-95/scaler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:d7f0f97954656f2b0c7f56b333a088e49015b6c56bfff5b7573a96773c36fbff
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size 988
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checkpoint-95/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:b5095e5fe129a9d18f44ea66bb15daa2478dbd199dc88ddbbce7a15cb2882ddf
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size 1064
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checkpoint-95/trainer_state.json
ADDED
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{
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"best_metric": 2.6642088414519094e-05,
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"best_model_checkpoint": "redmoon-gibberishdetective/checkpoint-95",
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"epoch": 1.0,
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"eval_steps": 500,
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"global_step": 95,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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"epoch": 1.0,
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"eval_accuracy": 1.0,
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"eval_loss": 2.6642088414519094e-05,
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"eval_runtime": 0.6769,
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"eval_samples_per_second": 1112.483,
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"eval_steps_per_second": 35.458,
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"step": 95
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}
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],
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"logging_steps": 500,
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"max_steps": 285,
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"num_input_tokens_seen": 0,
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"num_train_epochs": 3,
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"save_steps": 500,
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"stateful_callbacks": {
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"TrainerControl": {
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"args": {
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"should_epoch_stop": false,
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"should_evaluate": false,
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"should_log": false,
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"should_save": true,
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"should_training_stop": false
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},
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"attributes": {}
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}
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},
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"total_flos": 99747951187968.0,
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| 39 |
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"train_batch_size": 32,
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"trial_name": null,
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"trial_params": null
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}
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checkpoint-95/training_args.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:60997ebe145d3815febdbc269a01a0a4faca685b7dcdcdc18ab6f0d2908ff18a
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| 3 |
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size 5368
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