raghavdw/cci-capstone-asapp-empathy

Customer Service Empathy Model

Model Description

Empathy scoring model for customer service interactions. Predicts:

• Empathy Score (0-5)
• Active Listening Score (0-5)

This is part of a dual-model approach:

1. Intent model (available at raghavdw/cci-capstone-asapp)
2. This model (Empathy/Listening Scores)

Latest Training Info

{
  "training_args": {
    "output_dir": "models/test_run_20250110_162536/empathy_model",
    "overwrite_output_dir": false,
    "do_train": false,
    "do_eval": true,
    "do_predict": false,
    "eval_strategy": "epoch",
    "prediction_loss_only": false,
    "per_device_train_batch_size": 32,
    "per_device_eval_batch_size": 64,
    "per_gpu_train_batch_size": null,
    "per_gpu_eval_batch_size": null,
    "gradient_accumulation_steps": 1,
    "eval_accumulation_steps": null,
    "eval_delay": 0,
    "torch_empty_cache_steps": null,
    "learning_rate": 1e-05,
    "weight_decay": 0.01,
    "adam_beta1": 0.9,
    "adam_beta2": 0.999,
    "adam_epsilon": 1e-08,
    "max_grad_norm": 1.0,
    "num_train_epochs": 4,
    "max_steps": -1,
    "lr_scheduler_type": "linear",
    "lr_scheduler_kwargs": {},
    "warmup_ratio": 0.1,
    "warmup_steps": 0,
    "log_level": "passive",
    "log_level_replica": "warning",
    "log_on_each_node": true,
    "logging_dir": "models/test_run_20250110_162536/logs",
    "logging_strategy": "steps",
    "logging_first_step": true,
    "logging_steps": 10,
    "logging_nan_inf_filter": true,
    "save_strategy": "epoch",
    "save_steps": 500,
    "save_total_limit": 2,
    "save_safetensors": true,
    "save_on_each_node": false,
    "save_only_model": false,
    "restore_callback_states_from_checkpoint": false,
    "no_cuda": false,
    "use_cpu": false,
    "use_mps_device": false,
    "seed": 42,
    "data_seed": null,
    "jit_mode_eval": false,
    "use_ipex": false,
    "bf16": false,
    "fp16": false,
    "fp16_opt_level": "O1",
    "half_precision_backend": "auto",
    "bf16_full_eval": false,
    "fp16_full_eval": false,
    "tf32": null,
    "local_rank": 0,
    "ddp_backend": null,
    "tpu_num_cores": null,
    "tpu_metrics_debug": false,
    "debug": [],
    "dataloader_drop_last": false,
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    "dataloader_num_workers": 0,
    "dataloader_prefetch_factor": null,
    "past_index": -1,
    "run_name": "models/test_run_20250110_162536/empathy_model",
    "disable_tqdm": false,
    "remove_unused_columns": false,
    "label_names": null,
    "load_best_model_at_end": true,
    "metric_for_best_model": "eval_loss",
    "greater_is_better": false,
    "ignore_data_skip": false,
    "fsdp": [],
    "fsdp_min_num_params": 0,
    "fsdp_config": {
      "min_num_params": 0,
      "xla": false,
      "xla_fsdp_v2": false,
      "xla_fsdp_grad_ckpt": false
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    "fsdp_transformer_layer_cls_to_wrap": null,
    "accelerator_config": {
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      "even_batches": true,
      "use_seedable_sampler": true,
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      "gradient_accumulation_kwargs": null
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    "deepspeed": null,
    "label_smoothing_factor": 0.0,
    "optim": "adamw_torch",
    "optim_args": null,
    "adafactor": false,
    "group_by_length": false,
    "length_column_name": "length",
    "report_to": [],
    "ddp_find_unused_parameters": null,
    "ddp_bucket_cap_mb": null,
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    "dataloader_pin_memory": true,
    "dataloader_persistent_workers": false,
    "skip_memory_metrics": true,
    "use_legacy_prediction_loop": false,
    "push_to_hub": false,
    "resume_from_checkpoint": null,
    "hub_model_id": null,
    "hub_strategy": "every_save",
    "hub_token": "<HUB_TOKEN>",
    "hub_private_repo": false,
    "hub_always_push": false,
    "gradient_checkpointing": false,
    "gradient_checkpointing_kwargs": null,
    "include_inputs_for_metrics": false,
    "include_for_metrics": [],
    "eval_do_concat_batches": true,
    "fp16_backend": "auto",
    "evaluation_strategy": "epoch",
    "push_to_hub_model_id": null,
    "push_to_hub_organization": null,
    "push_to_hub_token": "<PUSH_TO_HUB_TOKEN>",
    "mp_parameters": "",
    "auto_find_batch_size": false,
    "full_determinism": false,
    "torchdynamo": null,
    "ray_scope": "last",
    "ddp_timeout": 1800,
    "torch_compile": false,
    "torch_compile_backend": null,
    "torch_compile_mode": null,
    "dispatch_batches": null,
    "split_batches": null,
    "include_tokens_per_second": false,
    "include_num_input_tokens_seen": false,
    "neftune_noise_alpha": null,
    "optim_target_modules": null,
    "batch_eval_metrics": false,
    "eval_on_start": false,
    "use_liger_kernel": false,
    "eval_use_gather_object": false,
    "average_tokens_across_devices": false
  },
  "final_loss": 0.006501355601283602
}

Usage Example

from transformers import AutoModelForSequenceClassification, AutoTokenizer

# Load empathy model
model = AutoModelForSequenceClassification.from_pretrained("raghavdw/cci-capstone-asapp-empathy")
tokenizer = AutoTokenizer.from_pretrained("raghavdw/cci-capstone-asapp-empathy")

# Process text
text = "I understand this must be frustrating for you"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)  # Returns [empathy_score, listening_score]

Last Updated: 2025-01-10 19:11:35