childes-segmentation-100k-gpt2_lm-model

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

• epoch: 4000.0
• eval_absolute_seg_boundary_fscore_Boundary Prediction: 0.6381
• eval_absolute_seg_boundary_fscore_Entropy: 0.4936
• eval_absolute_seg_boundary_fscore_Increase in Boundary Prediction: 0.6397
• eval_absolute_seg_boundary_fscore_Increase in Entropy: 0.6171
• eval_absolute_seg_boundary_fscore_Increase in Loss: 0.6068
• eval_absolute_seg_boundary_fscore_Increase in Rank: 0.6806
• eval_absolute_seg_boundary_fscore_Loss: 0.5355
• eval_absolute_seg_boundary_fscore_Majority Vote Cutoff: 0.7011
• eval_absolute_seg_boundary_fscore_Majority Vote Spike: 0.7273
• eval_absolute_seg_boundary_fscore_Rank: 0.5571
• eval_absolute_seg_type_fscore_Boundary Prediction: 0.1447
• eval_absolute_seg_type_fscore_Entropy: 0.2626
• eval_absolute_seg_type_fscore_Increase in Boundary Prediction: 0.3233
• eval_absolute_seg_type_fscore_Increase in Entropy: 0.3100
• eval_absolute_seg_type_fscore_Increase in Loss: 0.2509
• eval_absolute_seg_type_fscore_Increase in Rank: 0.4174
• eval_absolute_seg_type_fscore_Loss: 0.2412
• eval_absolute_seg_type_fscore_Majority Vote Cutoff: 0.4319
• eval_absolute_seg_type_fscore_Majority Vote Spike: 0.4164
• eval_absolute_seg_type_fscore_Rank: 0.2972
• eval_bpc: 4.4805
• eval_loss: 3.1056
• eval_model_preparation_time: 0.0008
• eval_perplexity: 22.3231
• eval_runtime: 47.9148
• eval_samples_per_second: 2.964
• eval_spike_seg_boundary_fscore_Boundary Prediction: 0.7308
• eval_spike_seg_boundary_fscore_Entropy: 0.5944
• eval_spike_seg_boundary_fscore_Increase in Boundary Prediction: 0.7195
• eval_spike_seg_boundary_fscore_Increase in Entropy: 0.6282
• eval_spike_seg_boundary_fscore_Increase in Loss: 0.6258
• eval_spike_seg_boundary_fscore_Increase in Rank: 0.6735
• eval_spike_seg_boundary_fscore_Loss: 0.5578
• eval_spike_seg_boundary_fscore_Majority Vote Cutoff: 0.7329
• eval_spike_seg_boundary_fscore_Majority Vote Spike: 0.7085
• eval_spike_seg_boundary_fscore_Rank: 0.6106
• eval_spike_seg_type_fscore_Boundary Prediction: 0.3885
• eval_spike_seg_type_fscore_Entropy: 0.2817
• eval_spike_seg_type_fscore_Increase in Boundary Prediction: 0.3610
• eval_spike_seg_type_fscore_Increase in Entropy: 0.2866
• eval_spike_seg_type_fscore_Increase in Loss: 0.3167
• eval_spike_seg_type_fscore_Increase in Rank: 0.3724
• eval_spike_seg_type_fscore_Loss: 0.2626
• eval_spike_seg_type_fscore_Majority Vote Cutoff: 0.4120
• eval_spike_seg_type_fscore_Majority Vote Spike: 0.3425
• eval_spike_seg_type_fscore_Rank: 0.3228
• eval_steps_per_second: 0.104
• step: 100000

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 30000
• training_steps: 100000

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu118
• Datasets 2.18.0
• Tokenizers 0.19.1