Upload Part 2 adamw: AdamW

part2/adamw/3epoch/metrics.json

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+{
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+ "category": "AdamW",
+ "config": {
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part2/adamw/3epoch/model.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7faa34742f415c09de4373cdf6d3157f015837c893764c32a96d269a5ed1424e
+size 207237524

part2/adamw/README.md

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+---
+tags: [anlp-assignment-2, optimizers, language-modeling, pytorch]
+language: [en]
+datasets: [browndw/human-ai-parallel-corpus]
+---
+# ANLP Assignment 2, Part 2: `adamw`
+
+Dense decoder-only transformer (Part 1 baseline architecture: 6 layers, d_model 512,
+8 heads, FFN hidden 2048, 51.7M params) pretrained from scratch for next-token
+prediction on `browndw/human-ai-parallel-corpus` with a from-scratch
+**AdamW** optimizer.
+
+Hyperparameters (from the LR sweep): `{"lr": 0.004}`; batch 32x256 tokens,
+warmup 3% + cosine to 10%, grad clip 1.0, bf16, dropout 0.
+
+| Checkpoint | Tokens | Val loss | Test loss | Test PPL | Test BLEU |
+|---|---|---|---|---|---|
+| `model.pt` (1x dataset, as specified) | 36,978,688 | 4.999 | 4.950 | 141.2 | 2.20 |
+| `3epoch/model.pt` (3 epochs) | 110,936,064 | 3.968 | 3.909 | 49.8 | 3.55 |
+
+BLEU: greedy continuation of the last 128 tokens of each test document's human
+opening, first 48 words scored (sacrebleu) against 7 references (human
+continuation + 6 LLM continuations).
+
+Files: `model.pt`, `3epoch/model.pt`, `base.yaml` + `adamw.yaml` (model/training/optimizer
+config), `final_hparams.json`, `tokenizer.json` (32k byte-level BPE, train split only),
+`metrics.json` / `3epoch/metrics.json` (full eval history every 0.1x dataset tokens).
+
+Training logs: https://wandb.ai/rakshitagg06-iiit-hyderabad/anlp-assignment2 (groups `part2-optimizers-1ep`, `part2-optimizers-3ep`).

part2/adamw/adamw.yaml

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+optimizer:
+  name: adamw
+  lr: 1.0e-3
+  betas: [0.9, 0.95]
+  eps: 1.0e-8
+  weight_decay: 0.1

part2/adamw/base.yaml

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+# Part 2 shared setup. The model is the Part 1 dense baseline (moe_baseline.yaml);
+# only the optimizer changes between runs (configs/part2/<optimizer>.yaml).
+ffn_type: mlp
+dropout: 0.0          # single-pass pretraining: no dropout
+model:
+  d_model: 512
+  ffn_hidden: 2048
+  max_seq_len: 256
+  num_heads: 8
+  num_layers: 6
+  vocab_size: 32000
+
+training:
+  seed: 42
+  epochs: 1             # 1x dataset (37.0M tokens), as the assignment specifies
+  batch_size: 32        # sequences per step
+  seq_len: 256          # packed blocks -> 8,192 tokens per step
+  warmup_frac: 0.03     # linear warmup over the first 3% of steps
+  min_lr_ratio: 0.1     # cosine decay to 10% of peak lr
+  grad_clip: 1.0
+  eval_every_frac: 0.1  # val loss + test BLEU every 0.1x dataset tokens
+  val_eval_blocks: 2048 # fixed val subset (524k tokens) for intermediate evals
+  log_every: 20
+  bleu_prompt_tokens: 128
+  bleu_new_tokens: 64
+  bleu_ref_words: 48

part2/adamw/final_hparams.json

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+{
+ "lr": 0.004
+}

part2/adamw/metrics.json

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+{
+ "optimizer": "adamw",
+ "category": "AdamW",
+ "config": {
+  "name": "adamw",
+  "lr": 0.004,
+  "betas": [
+   0.9,
+   0.95
+  ],
+  "eps": 1e-08,
+  "weight_decay": 0.1
+ },
+ "tag": "final",
+ "token_frac": 1.0,
+ "epochs": 1,
+ "steps_per_epoch": 4514,
+ "total_steps": 4514,
+ "total_tokens": 36978688,
+ "epoch_summaries": [
+  {
+   "epoch": 1,
+   "train_loss": 5.41453218460083,
+   "val_loss": 4.999754428863525
+  }
+ ],
+ "n_params": 51671040,
+ "optimizer_state_MB": 394.21875,
+ "peak_gpu_MB": 5975.31591796875,
+ "train_seconds": 817.8395464420319,
+ "tokens_per_second": 45215.08914661054,
+ "final_val_loss": 4.999754428863525,
+ "final_test_bleu": 2.198788506316811,
+ "full_val_loss": 4.9988884925842285,
+ "test_loss": 4.949979305267334,
+ "test_ppl": 141.17204237356978,
+ "history": [
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+   "eval_seconds": 20.693056106567383
+  },
+  {
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