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eval_outputs/openai-community/gpt2-xl-ckpt-14290/dialog_result_eval.json

@@ -0,0 +1,4 @@
+{
+    "rouge_l_f1": 11.070218865144792,
+    "status": "success"
+}

eval_outputs/openai-community/gpt2-xl-ckpt-14290/eval.json

@@ -0,0 +1,26 @@
+{
+    "dolly": {
+        "dataset_name": "Dolly",
+        "dataset_path": "./data/dolly/valid.jsonl",
+        "rouge_l_f1": 25.784589418800472,
+        "status": "success"
+    },
+    "sni": {
+        "dataset_name": "S-NI",
+        "dataset_path": "./data/sinst/11_/valid.jsonl",
+        "rouge_l_f1": 25.051588951850544,
+        "status": "success"
+    },
+    "self_instruct": {
+        "dataset_name": "Self-Instruct",
+        "dataset_path": "./data/self-inst/valid.jsonl",
+        "rouge_l_f1": 15.626907137888974,
+        "status": "success"
+    },
+    "vicuna": {
+        "dataset_name": "Vicuna",
+        "dataset_path": "./data/vicuna/valid.jsonl",
+        "rouge_l_f1": 16.35984222421401,
+        "status": "success"
+    }
+}

eval_outputs/openai-community/gpt2-xl-ckpt-14290/eval.log

@@ -0,0 +1,116 @@
+/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/cuda/__init__.py:61: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
+  import pynvml  # type: ignore[import]
+/mnt/hungpv/projects/ALM/run_eval.py:61: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
+  with torch.cuda.amp.autocast(dtype=torch.float16):
+
+Evaluating on Dolly...
+
+
+Dolly - Seed 50 ROUGE-L F1: 26.32%
+Dolly ROUGE-L F1: 26.32%
+
+Evaluating on S-NI...
+
+
+Traceback (most recent call last):
+  File "/mnt/hungpv/projects/ALM/run_eval.py", line 82, in <module>
+    main()
+  File "/mnt/hungpv/projects/ALM/run_eval.py", line 62, in main
+    results = evaluator.evaluate_multiple_benchmarks(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/mnt/hungpv/projects/ALM/evaluator.py", line 236, in evaluate_multiple_benchmarks
+    score = self.evaluate_benchmark_dataset(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/mnt/hungpv/projects/ALM/evaluator.py", line 134, in evaluate_benchmark_dataset
+    generated_responses = self.model.generate(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 2597, in generate
+    result = self._sample(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 3548, in _sample
+    while self._has_unfinished_sequences(this_peer_finished, synced_gpus, device=input_ids.device):
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 2748, in _has_unfinished_sequences
+    elif this_peer_finished:
+KeyboardInterrupt
+/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/cuda/__init__.py:61: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
+  import pynvml  # type: ignore[import]
+/mnt/hungpv/projects/ALM/run_eval.py:61: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
+  with torch.cuda.amp.autocast(dtype=torch.float16):
+
+Evaluating on Dolly...
+
+
+Dolly - Seed 50 ROUGE-L F1: 25.78%
+Dolly ROUGE-L F1: 25.78%
+
+Evaluating on S-NI...
+
+
+S-NI - Seed 50 ROUGE-L F1: 25.05%
+S-NI ROUGE-L F1: 25.05%
+
+Evaluating on Self-Instruct...
+
+
+Self-Instruct - Seed 50 ROUGE-L F1: 15.63%
+Self-Instruct ROUGE-L F1: 15.63%
+
+Evaluating on Vicuna...
+
+
+Vicuna - Seed 50 ROUGE-L F1: 16.36%
+Vicuna ROUGE-L F1: 16.36%
+
+Evaluating on dialog...
+
+
+Traceback (most recent call last):
+  File "/mnt/hungpv/projects/ALM/run_eval.py", line 82, in <module>
+    main()
+  File "/mnt/hungpv/projects/ALM/run_eval.py", line 71, in main
+    result = evaluator.evaluate_benchmark_dataset(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/mnt/hungpv/projects/ALM/evaluator.py", line 134, in evaluate_benchmark_dataset
+    generated_responses = self.model.generate(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 2597, in generate
+    result = self._sample(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 3557, in _sample
+    outputs = self(**model_inputs, return_dict=True)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 1210, in forward
+    transformer_outputs = self.transformer(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 939, in forward
+    outputs = block(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 439, in forward
+    feed_forward_hidden_states = self.mlp(hidden_states)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 365, in forward
+    hidden_states = self.act(hidden_states)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/activations.py", line 47, in forward
+    return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi) * (input + 0.044715 * torch.pow(input, 3.0))))
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 766.00 MiB. GPU 1 has a total capacity of 39.39 GiB of which 154.00 MiB is free. Including non-PyTorch memory, this process has 39.23 GiB memory in use. Of the allocated memory 31.84 GiB is allocated by PyTorch, and 6.89 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

eval_outputs/outputs/gpt2_120M_distill_v2/4998/dialog_result_eval.json

@@ -0,0 +1,4 @@
+{
+    "rouge_l_f1": 10.440596149582786,
+    "status": "success"
+}

eval_outputs/outputs/gpt2_120M_distill_v2/4998/eval.json

@@ -0,0 +1,26 @@
+{
+    "dolly": {
+        "dataset_name": "Dolly",
+        "dataset_path": "./data/dolly/valid.jsonl",
+        "rouge_l_f1": 20.86252865752882,
+        "status": "success"
+    },
+    "sni": {
+        "dataset_name": "S-NI",
+        "dataset_path": "./data/sinst/11_/valid.jsonl",
+        "rouge_l_f1": 17.76368508249188,
+        "status": "success"
+    },
+    "self_instruct": {
+        "dataset_name": "Self-Instruct",
+        "dataset_path": "./data/self-inst/valid.jsonl",
+        "rouge_l_f1": 10.654365939485007,
+        "status": "success"
+    },
+    "vicuna": {
+        "dataset_name": "Vicuna",
+        "dataset_path": "./data/vicuna/valid.jsonl",
+        "rouge_l_f1": 14.763177214107134,
+        "status": "success"
+    }
+}

eval_outputs/outputs/gpt2_120M_distill_v2/4998/eval.log

@@ -0,0 +1,132 @@
+/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/cuda/__init__.py:61: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
+  import pynvml  # type: ignore[import]
+/mnt/hungpv/projects/ALM/run_eval.py:59: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
+  with torch.cuda.amp.autocast(dtype=torch.float16):
+
+Evaluating on Dolly...
+
+
+Dolly - Seed 10 ROUGE-L F1: 17.11%
+
+Traceback (most recent call last):
+  File "/mnt/hungpv/projects/ALM/run_eval.py", line 80, in <module>
+    main()
+  File "/mnt/hungpv/projects/ALM/run_eval.py", line 60, in main
+    results = evaluator.evaluate_multiple_benchmarks(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/mnt/hungpv/projects/ALM/evaluator.py", line 236, in evaluate_multiple_benchmarks
+    score = self.evaluate_benchmark_dataset(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/mnt/hungpv/projects/ALM/evaluator.py", line 134, in evaluate_benchmark_dataset
+    generated_responses = self.model.generate(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
+    return func(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 2597, in generate
+    result = self._sample(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/generation/utils.py", line 3560, in _sample
+    outputs = model_forward(**model_inputs, return_dict=True)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 1210, in forward
+    transformer_outputs = self.transformer(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 939, in forward
+    outputs = block(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 403, in forward
+    attn_output, self_attn_weights = self.attn(
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
+    return forward_call(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+  File "/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 298, in forward
+    query_states = query_states.view(shape_q).transpose(1, 2)
+KeyboardInterrupt
+/home/hungpv/miniconda3/envs/span_fdd/lib/python3.10/site-packages/torch/cuda/__init__.py:61: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
+  import pynvml  # type: ignore[import]
+/mnt/hungpv/projects/ALM/run_eval.py:59: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
+  with torch.cuda.amp.autocast(dtype=torch.float16):
+
+Evaluating on Dolly...
+
+
+Dolly - Seed 10 ROUGE-L F1: 20.44%
+
+Dolly - Seed 20 ROUGE-L F1: 41.41%
+
+Dolly - Seed 30 ROUGE-L F1: 62.94%
+
+Dolly - Seed 40 ROUGE-L F1: 84.09%
+
+Dolly - Seed 50 ROUGE-L F1: 104.31%
+Dolly ROUGE-L F1: 20.86%
+
+Evaluating on S-NI...
+
+
+S-NI - Seed 10 ROUGE-L F1: 18.04%
+
+S-NI - Seed 20 ROUGE-L F1: 35.51%
+
+S-NI - Seed 30 ROUGE-L F1: 53.34%
+
+S-NI - Seed 40 ROUGE-L F1: 71.22%
+
+S-NI - Seed 50 ROUGE-L F1: 88.82%
+S-NI ROUGE-L F1: 17.76%
+
+Evaluating on Self-Instruct...
+
+
+Self-Instruct - Seed 10 ROUGE-L F1: 11.01%
+
+Self-Instruct - Seed 20 ROUGE-L F1: 20.69%
+
+Self-Instruct - Seed 30 ROUGE-L F1: 31.71%
+
+Self-Instruct - Seed 40 ROUGE-L F1: 42.29%
+
+Self-Instruct - Seed 50 ROUGE-L F1: 53.27%
+Self-Instruct ROUGE-L F1: 10.65%
+
+Evaluating on Vicuna...
+
+
+Vicuna - Seed 10 ROUGE-L F1: 14.40%
+
+Vicuna - Seed 20 ROUGE-L F1: 29.22%
+
+Vicuna - Seed 30 ROUGE-L F1: 44.40%
+
+Vicuna - Seed 40 ROUGE-L F1: 58.70%
+
+Vicuna - Seed 50 ROUGE-L F1: 73.82%
+Vicuna ROUGE-L F1: 14.76%
+
+Evaluating on dialog...
+
+
+dialog - Seed 10 ROUGE-L F1: 10.61%
+
+dialog - Seed 20 ROUGE-L F1: 20.88%
+
+dialog - Seed 30 ROUGE-L F1: 31.35%
+
+dialog - Seed 40 ROUGE-L F1: 41.79%
+
+dialog - Seed 50 ROUGE-L F1: 52.20%
+dialog ROUGE-L F1: 10.44%

eval_outputs/outputs/gpt2_120M_distill_v2/7140/dialog_result_eval.json

@@ -0,0 +1,4 @@
+{
+    "rouge_l_f1": 10.168257922801914,
+    "status": "success"
+}

eval_outputs/outputs/gpt2_120M_distill_v2/7140/eval.json

@@ -0,0 +1,26 @@
+{
+    "dolly": {
+        "dataset_name": "Dolly",
+        "dataset_path": "./data/dolly/valid.jsonl",
+        "rouge_l_f1": 20.77205179572258,
+        "status": "success"
+    },
+    "sni": {
+        "dataset_name": "S-NI",
+        "dataset_path": "./data/sinst/11_/valid.jsonl",
+        "rouge_l_f1": 17.566700218419037,
+        "status": "success"
+    },
+    "self_instruct": {
+        "dataset_name": "Self-Instruct",
+        "dataset_path": "./data/self-inst/valid.jsonl",
+        "rouge_l_f1": 10.534277780054138,
+        "status": "success"
+    },
+    "vicuna": {
+        "dataset_name": "Vicuna",
+        "dataset_path": "./data/vicuna/valid.jsonl",
+        "rouge_l_f1": 15.10137387900088,
+        "status": "success"
+    }
+}

gpt2_120M_distill_v2/7140/config.json

@@ -0,0 +1,38 @@
+{
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "use_cache": true,
+  "vocab_size": 50257
+}

gpt2_120M_distill_v2/7140/generation_config.json

@@ -0,0 +1,6 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.52.4"
+}

gpt2_120M_distill_v2/7140/model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1a69b532e7d363c1ac547c09dffc3080016033c5e5a5ee4432741d8d88db6f39
+size 497774208

gpt2_120M_distill_v2/args.yaml

@@ -0,0 +1,103 @@
+alm_diff_fn: binary_ce
+alm_mode: merge_by_space_prob+append_space
+binarization_temp: 100.0
+chat_template_mode: direct_encode
+data:
+  batch_size: 16
+  kind: jsonl
+  lang_code: en
+  num_workers: 16
+  path: data/dolly_train.jsonl
+debug: false
+distill_chunk_sizes:
+- 1
+distill_main_path_denominator: chunk_count
+distill_main_path_numerator: chunk_count
+do_cost_analysis: false
+dry_run: false
+dtype: bfloat16
+eval:
+  add_bos: true
+  chat_template_mode: direct_encode_no_force_eos
+  confirm_run_unsafe_code: true
+  lengths:
+  - 2048
+  limit: null
+  tasks:
+  - math_500_openmath2
+  - gsm8k_openmath2
+  tokens_per_batch: 16384
+eval_at_step_zero: false
+eval_interval: 50000
+expand_input_ids: false
+export_to_gcs_bucket: null
+gradient_checkpointing: false
+hypernet:
+  architecture: identity
+  multiply_hidden_dim_by_num_embeddings: true
+  num_heads: 16
+  num_layers: 1
+  residual: true
+  residual_alpha: 1
+  shared: true
+  use_attention: false
+  use_attention_mask: false
+latents_chunks: naive
+latents_do_project: true
+latents_normalization: l2_channelwise
+latents_to_align: last_hidden_state
+log_interval: 50
+loss_mask_mode: dolly
+loss_schedules: null
+loss_weights: null
+losses:
+- sft
+- alm_unconstrained
+max_student_length: 256
+max_teacher_length: 256
+model_lora_alpha: 64
+model_lora_rank: 64
+multitask_aggregation_fn: null
+n_data_parallel: 1
+n_model_parallel: 1
+name: gpt2_120m_distill
+num_workers: 24
+optimizer:
+  b1: 0.9
+  b2: 0.95
+  eps: 1.0e-08
+  grad_acc_steps: 1
+  learning_rate: 5.0e-05
+  max_grad_norm: null
+  param_groups:
+  - lr_scale: 2
+    pattern: .*(projector_query|projector_s2t|projector_t2s|projector_latents|loss_weights).*
+  type: adamw
+  weight_decay: 0.0
+output: outputs/gpt2_120M_distill_v2
+output_embeddings_mode: preserve
+pad_to_multiple_of: 64
+ppl_eval_data: null
+save_at_step_zero: false
+save_interval: 50000
+seed: 1234
+skip_lm_eval: true
+space_mask_mode: space+tab+newline+special
+steps: 7200
+student:
+  pretrained_model_name_or_path: openai-community/gpt2
+  revision: null
+  tokenizer_name: openai-community/gpt2:source=GPT2
+sync_interval: 100
+target_tokenizer_name: openai-community/gpt2:source=GPT2
+teacher:
+  pretrained_model_name_or_path: VoCuc/Qwen1.5_1.8B_SFT
+  revision: null
+  tokenizer_name: VoCuc/Qwen1.5_1.8B_SFT:source=Qwen2
+tokenizer_pair_bias_threshold: 0.1
+tokenizer_pair_data_path: artifacts/tokenizer_data/math_llama3_to_gemma2
+tokens_to_add: []
+train_embeddings: true
+train_model_mode: full
+use_chat_template: false
+warmup_steps: 500

gpt2_xl_distill/14290/README.md

@@ -0,0 +1,207 @@
+---
+base_model: openai-community/gpt2-xl
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:openai-community/gpt2-xl
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

gpt2_xl_distill/14290/adapter_config.json

@@ -0,0 +1,37 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "openai-community/gpt2-xl",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": true,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 8,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 256,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "c_proj",
+    "c_attn"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

gpt2_xl_distill/14290/adapter_model.safetensors

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+oid sha256:a83c4da369b6b1220180f3855a9794fbb65d7a2d0b6aa645d8a6a177e29654e3
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gpt2_xl_distill/args.yaml

@@ -0,0 +1,103 @@
+alm_diff_fn: binary_ce
+alm_mode: merge_by_space_prob+append_space
+binarization_temp: 100.0
+chat_template_mode: direct_encode
+data:
+  batch_size: 8
+  kind: jsonl
+  lang_code: en
+  num_workers: 16
+  path: data/dolly_train.jsonl
+debug: false
+distill_chunk_sizes:
+- 1
+distill_main_path_denominator: chunk_count
+distill_main_path_numerator: chunk_count
+do_cost_analysis: false
+dry_run: false
+dtype: bfloat16
+eval:
+  add_bos: true
+  chat_template_mode: direct_encode_no_force_eos
+  confirm_run_unsafe_code: true
+  lengths:
+  - 2048
+  limit: null
+  tasks:
+  - math_500_openmath2
+  - gsm8k_openmath2
+  tokens_per_batch: 16384
+eval_at_step_zero: false
+eval_interval: 50000
+expand_input_ids: false
+export_to_gcs_bucket: null
+gradient_checkpointing: false
+hypernet:
+  architecture: identity
+  multiply_hidden_dim_by_num_embeddings: true
+  num_heads: 16
+  num_layers: 1
+  residual: true
+  residual_alpha: 1
+  shared: true
+  use_attention: false
+  use_attention_mask: false
+latents_chunks: naive
+latents_do_project: false
+latents_normalization: l2_channelwise
+latents_to_align: last_hidden_state
+log_interval: 50
+loss_mask_mode: dolly
+loss_schedules: null
+loss_weights: null
+losses:
+- sft
+- alm_unconstrained
+max_student_length: 256
+max_teacher_length: 256
+model_lora_alpha: 64
+model_lora_rank: 64
+multitask_aggregation_fn: null
+n_data_parallel: 1
+n_model_parallel: 1
+name: TinyLLaMA_distill
+num_workers: 24
+optimizer:
+  b1: 0.9
+  b2: 0.95
+  eps: 1.0e-08
+  grad_acc_steps: 1
+  learning_rate: 0.0005
+  max_grad_norm: null
+  param_groups:
+  - lr_scale: 2
+    pattern: .*(projector_query|projector_s2t|projector_t2s|projector_latents|loss_weights).*
+  type: adamw
+  weight_decay: 0.0
+output: outputs/gpt2_xl_distill
+output_embeddings_mode: preserve
+pad_to_multiple_of: 64
+ppl_eval_data: null
+save_at_step_zero: false
+save_interval: 50000
+seed: 1234
+skip_lm_eval: true
+space_mask_mode: space+tab+newline+special
+steps: 15000
+student:
+  pretrained_model_name_or_path: openai-community/gpt2-xl
+  revision: null
+  tokenizer_name: openai-community/gpt2-xl:source=GPT2
+sync_interval: 100
+target_tokenizer_name: openai-community/gpt2-xl:source=GPT2
+teacher:
+  pretrained_model_name_or_path: VoCuc/Qwen2.5-7B-Instruct-Dolly-SFT
+  revision: null
+  tokenizer_name: VoCuc/Qwen2.5-7B-Instruct-Dolly-SFT:source=Qwen2
+tokenizer_pair_bias_threshold: 0.1
+tokenizer_pair_data_path: artifacts/tokenizer_data/math_llama3_to_gemma2
+tokens_to_add: []
+train_embeddings: true
+train_model_mode: lora
+use_chat_template: false
+warmup_steps: 1500